Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis

Facebook provides hospitals many potential benefits but also forces them to adapt the way they connect with their stakeholders in various fields of application. Within these fields of application hospitals can act in various roles. Hospitals might influence these roles, but they are also dependent on how they are perceived by their Facebook community. In this paper, we aim to find out how hospitals differ in the perception by their Facebook communities and how these differences can be measured. Furthermore, we develop hypotheses with image strength and identity diffusion as factors influencing how hospitals are perceived by their Facebook communities. We test our hypotheses with data of all hospitals in Switzerland. Our statistical analysis provides strong support for all of our hypotheses. Our findings might help hospitals better to assess their position in their Facebook community and to adapt their intended roles as well as their strategies, content, and behavior in accordance to that.

Background. Topic modelling is a method of automated probabilistic detection of topics in a text collection. Use of topic modelling for short texts, e.g. tweets or search engine queries, is complicated due to their short length and grammatical flaws, including broken word order, abbreviations, and contamination of different languages. At the same time, as our research shows, human coding cannot be perceived as a baseline for topic quality assessment. Objectives. We use biterm topic model (BTM) to test the relations between two topic quality metrics independent from topic coherence with the human topic interpretability. Topic modelling is applied to three cases of conflictual Twitter discussions in three different languages, namely the Charlie Hebdo shooting (France), the Ferguson unrest (the USA), and the anti-immigrant bashings in Biryulevo (Russia), which represent, respectively, a global multilingual, a large monolingual, and a mid-range monolingual type of discussions. Method. First, we evaluate the human baseline coding by providing evidence for the Russian case on the coding by two pairs of coders who have varying levels of knowledge of the case. We then measure the quality of modelling on the level of topics by looking at topic interpretability (by experienced coders), topic robustness, and topic saliency. Results. The results of the experiment show that: 1) the idea of human coding as baseline needs to be rejected; 2) topic interpretability, robustness, and saliency can be inter-related; 3) the multilingual discussion performs better than the monolingual ones in terms of interdependence of the metrics. Conclusion. We formulate the idea of an ‘ideal topic’ that rethinks the goal of topic modelling towards finding a smaller number of good topics rather instead of maximization of the number of interpretable topics.

The replication crisis has further eroded the public’s trust in science. Many famous studies, even published in renowned journals, fail to produce the same results when replicated by other researchers. While this is the outcome of several problems in research, one aspect has gotten critical attention—reproducibility. The term reproducible research refers to studies that contain all materials necessary to reproduce the scientific results by other researchers. This allows others to identify flaws in calculations and improve scientific rigor. In this paper, we show a workflow for reproducible research using the R language and a set of additional packages and tools that simplify a reproducible research procedure.

Posters are widely used a powerful tool for communication. They are very informative but are normally viewed for only 3 s, which calls for efficient and effective information delivery. It is thus important to know where people would look for posters. Saliency models could be of great help where expensive and time-consuming eye-tracking experiment isn’t an option. However, current datasets for saliency model training mainly deal with natural scenes, which makes research on saliency models for posters difficult. To address this problem, we collected 1700 high-quality posters as well as their eye-tracking data where each image is viewed by 15 participants. This could be the groundwork for future research in the field of saliency prediction for posters. It is noticeable that posters are rich in texts (e.g. title, slogan, description paragraph). The various types of texts serve respective functions, making some relatively more important than others. Nevertheless, the difference is largely neglected in current studies where researchers put same emphasis on all text regions, and the problem is especially crucial when it comes to saliency model for posters. Our further analysis of the eye-tracking results with focus on text offers some insights into the issue.

Web accessibility is an essential aspect in nowadays technologically ever-advancing societies as it promotes equality and inclusiveness of those people with different kind of disabilities, such as visual impairment. This article examined the accessibility of one Chilean University’s Virtual Library platform in order to generate significant improvements and to make it more accessible for visually impaired students. To do so, the present research used a mixed method approach, which included heuristic usability evaluation, user experience evaluation through the usability test involving real users, and both automatic and manual evaluations of accessibility. Results revealed that the most remarkable accessibility issues were related to the general structure of the website and the user control of the moving elements. Based on the information gathered through the different evaluations, it was possible to outline a proposal for changes to the University’s Virtual Library platform. The proposed changes were subsequently implemented, resulting in the platform’s compliance with the A and AA levels.

Energy saving activities are human activities to reduce energy consumption. These activities can be an effective measure to reduce energy consumption and humans can start them immediately, so it is expected as a measure against resource depletion and increased carbon dioxide emissions. In this context, there have been attempts made from various viewpoints based on the knowledge that the improvement of understanding it would lead to putting it into practice. However, the results of a questionnaire survey on energy saving activities have indicated that there is a gap between understanding and in-practice regarding energy saving, and improvement of understanding does not lead to in-practice. From this point, it is expected not to improving the understanding, but to propose a method that gives direct motivation for energy saving activities. In this study, we focus on@“vanity”, which is considered to be one of human needs for promoting energy saving activities. Here, “vanity” means a desire to pretend to be something good they are not. The purpose of this study is to consider experimentally whether energy saving activities could be applied to the target of vanity. At first, we will consider a method of applying vanity for energy saving activities and construct an experimental system to experimentally verify whether or not vanity could act as a motivation to promote energy saving activities. The experiment will be conducted using the experimental system to check if there are any persons who activate vanity regarding energy saving activities.

Whenever there are no vehicles ahead and there is good road visibility, drivers tend to exceed speed limits even when they normally take care to drive safely. However, in some of these cases, overspeeding may cause serious accidents. In this research, to encourage driving at safe speeds, we propose a system that uses a mobile device installed in a car to visualize a virtual front vehicle. Specifically, when the speed of the real car is faster, the size of the visualized vehicle becomes bigger, as though the driver were approaching the virtual front vehicle. That is, the size simulates approaching the front vehicle. On the other hand, when the speed is slower, the size becomes smaller, as though the front vehicle were moving further away from the driver. We expect that a driver will feel a sense of approaching the front vehicle, notice their fast driving speed from the size of the virtual front vehicle, and slow down. To verify this effect, we conducted a driving simulation experiment.

Innovation communities have been a focus of research over the last decade to foster and analyze how businesses and the public sector can engage customers or citizens to co-create products, strategies or services. While an applied and professional community management is seen as key, most initiators still do not understand the different personas and characters about their communities to adjust their management on an individual level and to embrace further potentials. In this paper, we analyzed 64 communities to pinpoint 11 different personas, which can be found repeatedly on either public or industry driven innovation communities. Based on our findings about their characteristics, motivation triggers and behavior on innovation communities, we offer managerial implications to enhance strategies and community management systems of innovation communities.

Survey tools are the main support for the development of reading comprehension evaluation instruments. The functionalities provided in the questionnaires design are the fundamental pillar to elaborate studies to evaluate in depth the reading comprehension and metacognitive strategies used. Survey tools are the main support for the development of reading comprehension evaluation instruments. Questionnaires design in available survey tools are based primarily on open, closed, multiple choice, or mixed questions. The functionalities provided in the questionnaires design are the fundamental pillar to elaborate studies to evaluate in depth the reading comprehension and metacognitive strategies used. However, current survey tools do not provide the required functionalities (i.e., types of questions) to design studies/questionnaires that allow the development of reading tasks that examine the students’ strategic potential.

We examine the satisficing respondent behavior and cognitive load of the participants in particular web survey interfaces applying automatic forwarding (AF) or manual forwarding (MF) in order to forward respondents to the next item. We create a theoretical framework based on the Cognitive Load theory (CLT), Cognitive Theory of Multimedia Learning (CTML) and Survey Satisficing Theory taken also into account the latest findings of cognitive neuroscience. We develop a new method in order to measure satisficing responding in web surveys. We argue that the cognitive response process in web surveys should be interpreted starting at the level of sensory memory instead of at the level of working memory. This approach allows researchers to analyze an accumulation of cognitive load across the questionnaire based on observed or hypothesized eye-movements taken into account the interface design of the web survey. We find MF reducing both average item level response times as well as the standard deviation of item-level response times. This suggests support for our hypothesis that the MF interface as a more complex design including previous and next buttons increases satisficing responding generating also the higher total cognitive load of respondents. The findings reinforce the view in HCI that reducing the complexity of interfaces and the presence of extraneous elements reduces cognitive load and facilitates the concentration of cognitive resources on the task at hand. It should be noted that the evidence is based on a relatively short survey among university students. Replication in other settings is recommended.

Multi-view clustering is a complex problem that consists in extracting partitions from multiple representations of the same objects. In text mining and natural language processing, such views may come in the form of word frequencies, topic based representations and many other possible encoding forms coming from various vector space model algorithms. From there, in this paper we propose a clustering fusion algorithm that takes clustering results acquired from multiple vector space models of given documents, and merges them into a single partition. Our fusion method relies on an information theory model based on Kolmogorov complexity that was previously used for collaborative clustering applications. We apply our algorithm to different text corpuses frequently used in the literature with results that we find to be very satisfying.

In many poster designs, an image usually will be used as a back-ground image, and text and picture will be carried out on the background image later. For intelligent layout design, cropping a suitable background image should be the first problem to be solved. In this paper, through eye movement experiments, ground truth saliency maps of the posters are obtained. Then, the characteristics of the saliency maps of background images are summarized. The characteristics are mainly the rules of the location and size of the salient areas in the background image. The research found that the salient areas of the poster background images are more concentrated in the upper and middle of the poster image, and they are distributed in an inverted triangle. These rules can cut a more suitable background image for typesetting.

Social live streaming services (SLSSs), a kind of synchronous social networking service, are slowly but surely becoming a part of people’s daily lives. To keep users interested, a wide range of gamification elements are implemented on these services, increasing the user engagement and changing their behavior. This study examined 20 different SLSS mobile applications and the applied gamification elements. A literature review as well as a content analysis were used to find appropriate SLSS apps and game elements. What kind of mechanics can be found on SLSS mobile apps and how many are implemented on each system? On three of the observed apps we could identify all game elements. Chinese SLSS apps are the most gamified ones. On Ustream, no game element is implemented. The game mechanics following others as well as customization are the most often applied; capturing a moment of a stream is the least often implemented.

The identification of coordinated campaigns within Social Media is a complex task that is often hindered by missing labels and large amounts of data that have to be processed. We propose a new two-phase framework that uses unsupervised stream clustering for detecting suspicious trends over time in a first step. Afterwards, traditional offline analyses are applied to distinguish between normal trend evolution and malicious manipulation attempts. We demonstrate the applicability of our framework in the context of the final days of the Brexit in 2019/2020.

Personalisation algorithms play an important role in catering the information that is relevant to us. The best results are achieved by the algorithms when they monitor the user activity. Most of the algorithms adapt to the users’ personal preferences by filtering out the information that is irrelevant to the user. However, one of the criticisms of this process is that it is leading to informational bubbles called the filter bubbles which is a personal space of content familiar to the user, which would reinforce their confirmational biases or create informational blind spots. This phenomena however is highly debated. In this light, we propose an agent based model study, which tries to verify the implications claimed by the filter bubble theorists and also create an hypothetical environment that does not have a filter bubble and test difference in the information dispersion and opinion formation in both the environments.

With evolved streaming technologies and faster mobile broadband, more and more live streaming platforms emerge online and become very popular among the users. From general platforms for streaming everyday life (e.g., YouNow) or reporting on news events (e.g., Periscope), through platforms for streaming video games (e.g., Twitch) or certain artistic performances (e.g., Picarto), the range of the services became very wide. As in most social media domains and with new developments on the digital market, the question arises whether the new trends also bear new challenges and issues of legal or ethical nature. This study is a systematic literature review of international scientific research on live streaming and potential legal problems (N = 22) conducted in order to pursue this question. It also entails a short review of legal issues with live streaming in Germany, a country with relatively strict consumer laws (e.g., data privacy) as well as first laws aiming at getting better control over the social media companies and users (e.g., Network Enforcement Act). The most prevalent legal domain within research on live streaming are copyright and sports broadcasting laws. The still understudied areas appear to be privacy, personality rights, and youth protection regulations. The most prominent issue within German legal discourse is the classification of live streaming as a telemedia offer or a broadcast, the second one entailing more restrictions and requirements (e.g., a broadcasting license).

While some polarization is potentially beneficial for democracy, hyper-polarization can lead to political gridlock, tribalism, and even physical violence. Given the gravity of these concerns, we use data from 1,424 residents of Virginia, USA to investigate if media exposure is related to polarization. We explore if getting news from traditional media (e.g. television, radio, newspapers) or social media (e.g. Facebook, Twitter, news aggregators) predicts the likelihood of being polarized. Results reveal stark differences between liberals and conservatives. Polarized conservatives use radio talk shows and television for their news while polarized liberals are likely to get their news from newspapers, television, and various social media outlets. We then investigate if polarization influences social capital. We find that polarized conservatives express low levels of bridging capital while polarized liberals are more likely to express high levels of bonding capital. Media consumption also influences bridging and bonding capital. We also find that while being polarized does not predict civic engagement, media consumption does. We consider these results disturbing. At least among the political extremes, conservatives and liberals are informed by different sources. This lack of a shared information results in competing worldviews while providing little opportunity for finding common ground. This combination of high bonding, low bridging capital can explain the recent increase in “lethal partisanship” where groups not only disagree but also accept or even wish harm to their political opponents.

Although social networking sites (SNS) offer functionalities for large-scale online research, user behavior and, in particular, scale and factors of their dropout from SNS-administered research have hardly been studied. In this paper we present an SNS-based experiment and survey tool and report the results of our investigation of user dropout from a research that uses this tool. This research is a pilot stage of a cross-country comparative study of political fake news recognition. At this stage Facebook and Vkontakte users from Russia have been recruited via SNS ad managing systems, asked to evaluate the truthfulness of the displayed news items and to answer a number of questions. We find that although we had to perform thousands of ad displays, among those who clicked the ad dropout rate was 60 and 65% in Vkontakte and Facebook respectively. 1,816 complete questionnaires were collected within a few days. More educated respondents, people living in or near megalopolises and those who agreed to grant access to their Vkontakte account data were significantly more inclined to complete the survey, but the major predictor of dropout was high individual speed – an indicator of low interest. Neither device type (mobile vs desktop) nor the number of questions per screen (one vs two) affected dropout. The number of leavers declined from the first to the last screens of our tool, but transition from the experiment to the survey and demographic questions produced clear peaks in the dropout curve.

Illicit drugs are sold online. Besides cryptomarkets, young people today are also using social media to buy and sell different drugs. The aim of this nationwide study was to investigate the phenomenon of buying drugs from social media among American young people. Relatively few studies have investigated young people buying drugs online and, therefore, it is important to know more about the psychological and social risk factors of this behavior. The participants of the study were 15–25-year-olds from the U.S. (M = 20.05; 50.17% female). Buying drugs online was utilized as an outcome variable. The covariates included measures of impulsivity and delay of gratification, sense of belonging to online communities, online homophily, friends sharing risk material online, psychological distress, and measures for addictive behaviors including hazardous drinking, problem gambling, and compulsive Internet use. Results showed that buying drugs online is still a relatively rare phenomenon, but many of those buying drugs online used social media services to do so. Buying drugs online was associated with higher impulsivity and lower measures of delay discounting indicating self-control problems. Online buyers also had multiple problems with mental wellbeing, as they reported more psychological distress, problem gambling, and compulsive Internet use than those drug users who had not bought drugs online. The existence and comorbidity of these problems suggest that drug availability online might worsen their situation. As impulsive decisions are especially easy to make on social media, more focus should be placed on youth behavior on mainstream social media services.

Few studies have jointly explored the role of factors such as the use of social media, the personality characteristics of young people, the use of thinking mechanisms aimed at moral disengagement, and the emotions experienced in relation to cyberbullying and cybervictimisation behaviour. The analysis presented here, carried out through a questionnaire distributed online and filled in by 655 Italian high school students, allowed to highlight the relationships between these variables. In particular, it emerged that the phenomena of cyberbullying and cybervictimisation are related to the time spent online and to the mechanisms of moral disengagement, which in turn are related to the personality trait of agreeableness. Emotions experienced are most clearly positive in cases of cyberbullying and negative for the victims. This correspondence, however, is reversed in bullies who resort more to thoughts aimed at moral disengagement and feel more negative emotions. The same reversal seems to occur in the victims who, in correspondence with an increased use of the mechanisms of moral disengagement, report to feel more positive emotions.

The development and deployment of new technologies have influenced the media environment by enabling quick and effective dissemination of false news via social networks. Several experimental studies have highlighted the role of thinking style, social influence, source credibility and other factors when it comes to fake news recognition. Our study makes several contributions to existing knowledge. Web introduce a measure of conspiracy thinking, a comparison between politics and business news recognition, and we investigate the effects of sensationalist headlines on users’ abilities to differentiate between false and true news. 228 university students (203 completed the entire survey) from three departments (Humanities, Management, and Economics) took part in an online experiment. The results of a regression analysis demonstrate that double-checking of news online has a significant effect on individuals’ overall ability of differentiating between true and false news. Thinking styles, prior experience, and such control variables as age and gender have no significant effect on the overall level of accuracy. We also discuss the effects of different factors responsible for the accuracy of fake news recognition in business and political news, as well as several limitations of the study.

The automatic detection of rumors in social networks is an important problem that would allow counteracting the effects that the propagation of false information produces. We study the performance of deep learning architectures in this problem, analyzing ten different machines on word2vec and BERT. Our results show that some architectures are more suitable for some particular classes, suggesting that the use of committee machines would offer advantages in this task.

Within the last years, the perception of social media has dramatically changed in public opinion as the dark side of social media has become more and more visible. Previous research has tried to explain unethical behavior on social media with intrinsic and extrinsic motives. The main goal of this study is to develop and provide a conceptual model that links moral receptors with moral disengagement in the context of unethical behavior on social media. For that reason, a set of propositions are developed linking the moral receptors “harm/care,” “fairness/reciprocity,” “in-group/loyalty,” “authority/respect,” and “purity/sanctity” with moral disengagement in order to explain immoral conduct on social media.

This study investigates catfishing and online impersonation. Catfishing is a relatively new social phenomenon that happens online. The term, catfishing is still foreign to many online users. It is still unclear to many people what constitutes catfishing and how it is the same or different from online impersonation or phishing. In this paper, we discuss catfishing and how it relates to other online threats like online impersonation and phishing. To see how catfishing affects online users, we interviewed sixteen college students who use social media and online dating platforms at a Historically Black College and University. Among the sixteen participants, nine said they were catfish victims, and four said they were online impersonation victims. Three participants said they had catfished other people online. In this paper, we share the stories of catfish and catfish victims. Our findings show that catfishing has affected our participants’ social media use and prevented some of them from trying online dating services.

Content recommendations on big internet platforms such as YouTube are supported by crowd-based recommender systems. Users are presented with what other users in comparable situations spent time on. There are several examples, however, where sequences of suggested content quickly degenerated towards only slightly related, sometimes problematic content that we define as contextually inappropriate. We try to identify the basis of this effect from both the user and the technical side, and set up a simple simulation system in order to better understand the interactions. Simulation results provide evidence that autoplay is an especially problematic feature, but that completely preventing inappropriate suggestions is technically very hard if not infeasible because it is the nature of a recommendation system to take into account feedback from the user and adapt to it. We also propose some possible measures to mitigate the problem.

Despite the existence of several studies on the characteristics and role of social bots in spreading disinformation related to politics, health, science and education, financial social bots remain a largely unexplored topic. We aim to shed light on this issue by investigating the activities of large social botnets in Twitter, involved in discussions about stocks traded in the main US financial markets. We show that the largest discussion spikes are in fact caused by mass-retweeting bots. Then, we focus on characterizing the activity of these financial bots, finding that they are involved in speculative campaigns aimed at promoting low-value stocks by exploiting the popularity of high-value ones. We conclude by highlighting the peculiar features of these accounts, comprising similar account creation dates, similar screen names, biographies, and profile pictures. These accounts appear as untrustworthy and quite simplistic bots, likely aiming to fool automatic trading algorithms rather than human investors. Our findings pave the way for the development of accurate detection and filtering techniques for financial spam. In order to foster research and experimentation on this novel topic, we make our dataset publicly available for research purposes.

Social media is an internet tool often used by businesses to communicate with customers, clients, vendors and other businesses. It is used for financial transactions with customers and to pay employees and manage the company. But social media and the internet are fraught with risks that businesses should be aware of, risks that could impact their company, their employees and their clients. Companies need to be aware of what the social media risks are and mitigations that can be taken to reduce those risks. While social media threats cannot be removed, actions can be taken to reduce the probability that they will be successful and to reduce the impact if they succeed. The impact of a threat gaining internet access to a business could cripple a company financially, others could damage relationships, but all would impact the company’s ability to grow and thrive.

Social media users are increasingly influenced by misinformation and disinformation as the techniques offer affordances to rapidly spread information to large groups of people. Most of the existing studies about misinformation and disinformation are in the context of Western cultures, the influence of misinformation in Chinese context is underexplored. To fill this research gap, this study analyzed 26,138 Weibo posts that are marked as containing misinformation. We performed a frequency analysis of these posts’ metadata and the top 50 frequent nouns, verbs, and adjectives in the dataset, and examined the sentiment in the content. Our results show that many posts that contain misinformation tactically target topics that Chinese people are already concerned about. The persuasion literature implies that these characteristics increase the persuasive power of the posts. With the forward-asking verbs are frequently used in the posts, one behavior that the receivers are persuaded to perform is to share these posts with the others, which can contribute to the virality of the misinformation. Another alarming finding is that a large proportion of our collected posts asked the receivers for help and the posts showed gratitude to acknowledge the forwarding and helping behavior. Based on the trust literature and the notion that trust as a social reality, we discuss the potentially severe negative impact these posts can impose on the society as they undermine Weibo users’ trustfulness to others and to the social media platform.

The internet has transformed the way that humans interact not only online, but also in real life. Through social networking sites and other community based online sites a person can amass multiple online identities through their active presence on different online platforms that can affect the user in the real world [2]. These identities can be home to different types of digital artifacts in the form of pictures, posts, or videos and are attached to a specific user. The combination of these identities can be used to create a digital narrative about the user which can then be used to create a timeline of the user’s life and their relationships. The content of this digital narrative is the property of the user that created it and can be considered their digital legacy. It is up to the user to determine how their digital legacy will be handled after their real-world death.

Background. The spread of affective content on social media, as well as user grouping based on affect [1], has been a focus of scholarly attention for over a decade. But, despite this, we lack evidence on what roles various particular emotions play in the dynamics of discussions on social media. Emotional contagion theory (Hatfield et al. 2014) adapted for social media suggests that diffusion of emotions happens on individual level, via direct one-time contact with emotionalized content [2]. Other theories, like theories of social influence or social learning [3], thought, suggest multiple, hierarchical, and/or topically-restricted contacts. The idea of affective agenda [4] implies that the dynamics of an emotional discussion needs to be assessed on the aggregate level. The question remains – what role the emotions taken on aggregate level play in the discussion dynamics, being either catalyzers or inhibitors of the discussions. One may suggest that emotions of different stance (positive/negative) may spur/slow down the discussions in various ways. Objectives. We analyze the spread of two polar emotions – anger and compassion – in three Twitter discussions on inter-ethnic conflicts, namely Ferguson protests (the USA, 2014), Charlie Hebdo massacre (France, 2015), and mass harassment in Cologne (Germany, 2015–2016). By analyzing the co-dynamics of the overall discussions and these two emotions we can conclude whether the pattern of the spread of emotions and its link with the discussion dynamics is the same in various language segments of Twitter. Data collection and methods. The data we use were collected by our patented Twitter crawler in the aftermath of the conflicts and include altogether over 2,5 M tweets. We used manual coding by native speakers and machine learning to detect the emotions; then, we visualized the dynamics of growth of the emotional content of the discussions and used Granger test to see whether anger or compassion gave a spur to the discussions. Results. We have received moderate results in terms of the dependence of the number of neutral users upon that of emotional users, but have spotted that the beginnings of the discussions, as well as the discussion outbursts, depend more on compassion, not on angry users, which needs more exploration. We have also shown that the hourly dynamics of emotions replicates that of the larger discussion, and the numbers of angry and compassionate users per hour highly correlate in all the cases.

With the advent of Web 2.0, the life of museums has undergone a profound change: today, almost all museums in the world use social media as a communication strategy with their visitors. However, only a few papers have analyzed the role of social media in attracting a greater number of visitors to museums.For this reason, the aim of this paper is to analyze how museums use social media to improve their relationship with visitors and, at the same time, to ensure a better positioning of museums on the market by increasing their number.We tried to find some answers in terms of checking whether a direct connection exists between the number of social media subscribers and the number of visitors to the museums. Secondly, we looked into the rating of museums on social media and analyzed whether ratings do indeed contribute to increasing the number of visitors.To answer these questions, we conducted a research on 14 museums which are considered to be “popular” – seven located in Bucharest, Romania and seven located in Paris, France. The reasons why we chose this mix of museums are the following: the chosen museums are representative for the two European capitals; there is a variety of social networks used by these museums, which indicates an ongoing interest (in the case of the French museum) or a more recent interest (in the case of the Romanian museums) for personalizing the relationship with visitors through social media. The qualitative and quantitative analysis carried out refers to the year 2018 and the data was collected from the selected museums’ official websites and their respective Facebook, Twitter, YouTube, TripAdvisor and Google pages.Also, as an added benefit from processing the information gathered through the specialized studies and from the statistical data regarding the museums, a “sketch” of both the typical French and the typical Romanian museum visitor was obtained. As one can expect, there are both similarities and differences between the two portraits, despite the fact that France and Romania have a similar cultural background. If the quantitative analysis suggests that the investment in social media is desirable, regardless of the size and notoriety of the museum, the qualitative analysis leads us to the conclusion that personalizing the relationship with visitors becomes a “must” for any museum regardless of its country of origin, in the sense of creating differentiated strategies for each type of visitor and, in particular, for Millennials, in terms of competitive advantage.

Digital communication has influenced our lives in a number of ways, and the focus in this paper is on how people obtain, share and interpret health and fitness related information in the context of a virtual community on a Croatian fitness forum. The Internet is proven to be the leading source of information in Croatia and health-related content is among the most represented coverage people seek online. The purpose in this paper is therefore to analyze information needs expressed by users of the biggest fitness forum in Croatia and to look into the topics represented on it. Also, the aim is to gain insight based on empirical results into the use of information communication technology to create and sustain a sense of belonging and mutual support in this virtual community. For this purpose, we conducted a qualitative subject and content analysis of posts on the most active place on the fitness.com.hr forum in 2019 (subcategory How to lose weight) and interviewed forum administrators and the most active forum members. Our results show that information needs of fitness forum users fall into six broader facets, all related to weight loss: nutrition, physical activity, psychological and health issues, personalized initial status, reporting results and other. Analysis also showed that a sense of belonging and emotional and peer support can in some ways be recognized in this fitness virtual community.

Gaze behavior, including eye contact and gaze direction, is an essential component of non-verbal communication, helping to facilitate human-to-human conversation in ways that have often been thought of as universal and innate. However, these have been shown to be influenced partially by cultural norms and background, and despite this, the majority of social robots do not have any cultural-based non-verbal behaviors and several lack any directional gaze capabilities at all. This study aims to observe how different gaze behaviors manifest during conversation as a function of culture as well as exposure to other cultures, by examining differences in behaviors such as duration of direct gaze, duration and direction of averted gaze, and average number of shifts in gaze, with the objective of establishing a baseline of Japanese gaze behavior to be implemented into a social robot. Japanese subjects were found to have much more averted gaze during a task that involves thinking as opposed to a task focused on communication. Subjects with significant experience living overseas were found to have different directional gaze patterns from subjects with little to no overseas experience, implying that non-verbal behavior patterns can change with exposure to other cultures.

More and more companies are putting emphasis on communication skill in the recruitment of their employees and adopt group discussion as part of their recruitment interview. In our ongoing project, we aim to develop a training system that can provide advices to its users in improving the perception of their communication skill during group discussion. In order to realize this goal, a conceptual unit of communicational behaviors and a template of communication style are required. We propose the use of functional roles of the participants in group discussions as this unit. In order to incorporate the use of functional roles for improving the perception of participants’ communication skill, the first task is automatic detection of the participants’ functional roles in real-time. We previously proposed a SVM based model for this task but the results were only moderate. We expect including temporal characteristics, frame-wise interaction of modalities, and inter-person interaction can improve the classification accuracy and explored the use of RNN based networks to see the effectiveness of these factors.

The paper discusses correlation between interlocutors’ eye-gaze behavior and their perceived personality traits in human-human and human-robot interactions. Given that personality is related to the person’s typical manners and styles of behaving, it can be assumed that such underlying characteristics are reflected in the person’s gaze patterns as well. Starting from the comparison of human-human and human-robot interaction, the participant’s gaze frequency and length in regard to the human vs. robot partner’s face and body are related to the participant’s perceived personality traits. A positive correlation is found concerning the differences in gaze patterns and the extrovert personality trait. This seems highly reasonable, considering the basic function of gaze as a means to collect situational information and the extrovert communication style as actively looking for new information.

This investigation focused on gender- and generation-determined differences regarding the need and use of Fitbit Facebook groups and the motivation to join these groups. Therefore, we applied the Uses and Gratifications Theory (U&GT) and Self-Determination Theory (SDT). This investigation aims to better understand the needs of activity tracking technology users who joined these groups. For this aim, we used an online survey. All in all, 268 participants are analyzed in this investigation. Results reveal that there are only a few gender- and generation-determined differences. This investigation draws on previous studies and allows to expand further research and to stress factors that needed to be considered.

Vehicles are being embedded with advanced technological capabilities and we are headed quickly towards completely self-driving cars. These same technologies will also enhance the convenience and safety features in all types of vehicles. The era of intelligent cars is here. Most vehicles manufactured and sold in 2019, that are not economy versions, include some form of adaptive cruise control, lane keeping assist, collision mitigation, video monitoring of adjacent lane obstructions, heads up display (HUD), and parking assist up to and including self-parking capabilities. With the plethora of new technologies being incorporated into our vehicles that are still controlled by us, how are we managing? According to anecdotal evidence gathered from several Honda dealerships in middle Tennessee many drivers aren’t satisfied with some of these capabilities. This paper attempts to explain the technologies available and in use, and the driver’s thoughts about partial assist technologies that are currently in place. While these features are designed to enhance safety and decrease traffic accidents, are they actually increasing driver safety or simply facilitating driver distraction? NTSB standards and recommendations will be summarized, and a questionnaire developed that helps us examine driver reaction to the technologies embedded in 2019 and 2020 Honda vehicles.

In this study, we analyzed whether interaction dynamics are related to emotional expressions within online gambling communities. As data, we used 8452 comments posted on Reddit gambling communities. The data were analyzed with sentiment analysis tool VADER and multilevel regression analysis. Results showed that comments were more positive when they were directed to other users and made by users with more interactive commenting behavior. Comments were less positive in those discussions that were most active and in those that mainly involved replies to other users. We also found that more positive posts received more positive commenting and negative posts received more negative comments. Overall, the activity and interactivity of communication and emotional correlation are associated with positive emotional expression in online communication. For negative emotions, we found evidence only for emotional correlation. Future studies should explore how interaction dynamics together with more contextual factors shape emotional expressions within online communities.

Recently, due to the expansion of TV or smart phone, the frequency of exposing media has increased. Also, the way of interacting with the media is diversifying by life stages or life balance. In such situations, people get much information about products and services on media. Therefore, it is important to select the best media for advertisement. In this study, we analyze the characteristics of exposing media using media exposure data. First, we performed Non-negative Matrix Factorization (NMF) to extract pattern of exposing media. Second, we used random forest to analyze the characteristics of the exposing media pattern. From our result, we discussed how to advertise on TV and website.

On 9th October 2019 an armed nationalist murdered two bypassing citizens in a killing spree directed at a synagogue in Halle, Germany. Instantly, a broad diffusion of information unfolded on Twitter. Traffic for tweets mentioning Halle reached a peak as high as a hundred times to average value of the days before. In this study we examine this immense increase in communication and observe temporal diffusion patterns in crisis communication. We compare the traffic of tweets generated in this incident against Twitter traffic persisted during two other crisis events as well as a regular trending topic. A discussion of information diffusion based on network theoretic measures during crisis and terror events is presented. Results show that active user’s behavior changes with the onset of the incidents in all events in focus–while popular user’s metrics are consistent throughout the data sets. actively tweeting and repeatedly engaging users are detected only in two data sets.

The purpose of this research is represented by the need to highlight the trend regarding the access and use of mobile banking and mobile payment services by student consumers, in close connection with the cultural factors that can influence this trend. In this regard, the paper considers aspects such as observing the students’ behavior regarding how mobile banking is used in the monitoring of bank accounts, taking financial decisions about saving and investments, as well as shopping. The research methodology addressed aimed at both qualitative and quantitative research, considering the mobile financial services offered by banks operating in Romania. The authors conducted a quantitative research based on a questionnaire, grouping selectively a multitude of questions on how students perceive mobile banking according to the specific interaction they had with it. The structural model that was used is called the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), a combination of UTAUT developed in 2003 by Venkatesh et al. and Hofstede’s cultural moderators. The qualitative analysis considered the placement of the factors analyzed in a cultural context linked with the Romanian students, trying to investigate the values, perceptions, desires, but also the stereotypes and prejudices taken from the family or other social organisms. The results of this research reveal how cultural factors determine the Romanian students attitude close to the use of mobile banking services. Factors that have a positive influence on behavioral intention are performance, facilitating conditions and habit. Habit has also a positive influence on use behaviour. Social influence has a negative effect on behavioral intention. There is no relationship between behavioral intention and effort expectancy, hedonic motivation and price value. Also, there is no association between use behavior and behavior intention. All cultural moderators signal a negative influence on the behavioral intention - use behavior relationship.

With the rapid development in artificial intelligence, social computing has evolved beyond social informatics toward the birth of social intelligence systems. This paper, therefore, takes initiatives to propose a social behaviour understanding framework with the use of deep neural networks for social and behavioural analysis. The integration of information fusion, person and object detection, social signal understanding, behaviour understanding, and context understanding plays a harmonious role to elicit social behaviours. Three systems, including depression detection, activity recognition and cognitive impairment screening, are developed to evidently demonstrate the importance of social intelligence. The study considerably contributes to the cumulative development of social computing and health informatics. It also provides a number of implications for academic bodies, healthcare practitioners, and developers of socially intelligent agents.

Materialism is a set of human values that places importance on the symbolic value of money or material goods. Furthermore, materialistic values have been associated with Internet usage, and also social media usage. The current research investigates this relationship further by specifically examining whether those with more materialistic values might use social media (Facebook) in different ways to those with less materialistic values. Self-report measures were collected from 108 participants. It was found that the higher the importance (extrinsic importance) attached to materialistic values, the more time spent posting photos, but the less time spent chatting on Facebook messenger and less time posting links. The higher the perceived likelihood (extrinsic likelihood) of achieving materialistic values, the more reported time posting status updates, but the less time spent chatting on Facebook messenger and less time posting links. Conversely, the higher the importance attached to non-materialistic values (intrinsic importance) the more reported time chatting on Facebook messenger, more time spent posting links, but less time spent posting photos. And the higher the reported likelihood of achieving non-materialistic values (intrinsic likelihood) the more reported time chatting on Facebook messenger, more time spent posting links, but less time spent posting status updates. However, neither self-reported time checking Facebook, nor self-reported attention paid to advertising were related to either materialistic or non-materialistic values. Overall, the findings indicate that certain activities on Facebook can be associated with both materialistic and non-materialistic values.

Nowadays, social networks have created a massive mean of communication, that was unthinkable many years ago. Informal communication, blogging, and online discussions have transformed the Web into a huge repository of remarks on numerous themes, producing a potential wellspring of data for various areas. In this paper we analyze, using Topic Models, a recent widespread feminist movement. Las Tesis is a feminist collective that initiated a protest against sexual abuse, and that was replicated in more than dozen different countries in matter of days. We use LDA and BTM to detect automatically the topics in over 627643 tweets that were gathered from the 25th November until the 5th January. The resulting topics obtained, from tweets in Spanish and English, show that these algorithms are able to capture the real-world events that occurred in Chile and Turkey.

Reddit is a social news service and information platform where users can discuss different topics in sub-communities, so called “subreddits.” In this study, the perceived information system quality and the perceived content quality of the information service Reddit, the information seeking behavior as well as the motives of Reddit’s users following the Uses and Gratifications Theory are analyzed differentiated by the perception of male and female users. To this end, a survey with 495 Reddit users was conducted. Results show that users’ motives to apply Reddit are mostly entertainment as well as information. All users agree that Reddit is enjoyable, useful, and easy to use, whereby no major difference in the perception by male and female users can be observed. All in all, the content is perceived as up-to-date and can be easily read and easily understood or comprehended. Most users are browsing through Reddit to find information, whereas male users are using the advanced search option more often than female users.

Mass self-communication [12] has led to a continuous process of de-institutionalization of media systems; today, myriads of bloggers are struggling to receive audiences’ attention. Networked user communities contribute to the creation of attitudes and transfer of information and ideas [6]. The two major approaches to reconstructing the discussion structure are the ‘issue mapping’ and the ‘actor mapping’. ‘Actor mapping’ focuses on a dataset of bloggers that is checked for interconnectedness and requires a development of a pre-defined list of bloggers; however, such lists are easy to create only in case of top political bloggers or journalists. This study aims to test a methodological approach of ‘actor mapping’ on Instagram; more precisely, we aim at testing a method for creating a corpus of relevant accounts on Instagram. The methodological design we have developed aims to create a database of Instagram blogs about migration in Russian language beyond an issue-triggered discussion. The paper discusses also the restrictions of Instagram as platform and contributes to the general knowledge how Instagram bloggers use hashtags.

Gaze is reported to have important functions in communication, such as expressing emotional states, exercising social control, highlighting the informational structure of speech, and coordinating floor-apportionment. For these reasons, studying these communicative functions is expected to contribute to HCI systems by identifying communication characteristics and the role of each participant. This study analyzes how the communicative functions of utterances affect the listener’s gazing activities from the viewpoint of grounding, based on a triadic corpus with newly labeled grounding tags. The results showed that the duration of a listener’s gaze is longer in second language (L2) conversations, in goal-oriented conversations, and during utterances presenting new information. These results suggest that linguistic proficiency, conversation topic, and grounding factors all affect a listener’s gazing activities, providing us with some information that could assist in the design of HCI, HRI, and CSCW systems that better reflect the interaction contexts and linguistic proficiency of users.

In this paper, we focus on social media users and examine the factors predicting users’ confidence in platforms in case of private messaging. For the social media platforms, social ties and information that flows through the contacts are valuable assets, which must be considered in the development of the services (such as messaging applications) in order to attract users. We use nationally representative data derived from surveys targeted at 15- to 74-year-old Finns (N = 3,724). The measures included user’s confidence in platform services in social messaging, trust in social ties on social media, size of social media networks, a wide selection of measures related to internet and social media behavior, and demographic factors. The results of the analysis supported the hypothesis that high confidence in platforms is strongly dependent on the social resources of users. Network size and trust in social ties were crucial variables in determining the confidence in social media platforms as a secure channel of private messages. The results also amplified that trust in social media networks has independent explanation power in the platform confidence apart from behavioral and demographic factors. The findings are significant in terms of understanding the contemporary information society and dynamics between platform services and users. The markets of social media platforms and other agents in the sector are dependent on the social resources of users, and especially on the social trust of users.