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This chapter examines privacy as a multilevel concept. While current conceptualizations of privacy tend to focus on the individual level, technological advancements are making group privacy increasingly important to understand. This chapter offers a typology of both groups and group privacy to establish a framework for conceptualizing how privacy operates beyond the individual level. The chapter describes several contemporary practices that influence the privacy of multiple actors and considers the dynamics of multi-stakeholder privacy decision-making. Potential tensions that exist between the rights and preferences of individual group members or between individuals and the group as a whole are also examined. Finally, recommendations for tools and other mechanisms to support collaborative privacy management and group privacy protection are provided.

Power is an integral part of group dynamics and when deception is involved, it affects the process of group decision-making as well as the outcomes of those decisions. We examined 95 groups playing a popular party card game called Mafia in which some players were randomly assigned the role of Spies, and others, the role of Villagers. Spies concealed their identity and deceived the other naive players (the Villagers), who were assumed to be truthful. Data were collected from University students around the world, including in Israel, Singapore, Hong Kong, Fiji, Zambia, and three locations within the U.S. The results revealed differences in the way that players from those different cultural locations exhibited dominance and rated the trustworthiness of other players. In general, more dominant players were seen as more trustworthy, although that was moderated by the cultural location. Spies (deceivers) were viewed as less dominant than Villagers (truth-tellers). Males were rated as more dominant, especially when in the Spy role. The implications for this study on the study of groups and power relations among group members are discussed.

Identifying the visual focus of attention (VFOA) in multi-person discussions is related to many types of social interactions such as dominance/deference, like/dislike, and trust/distrust relationships. However, identifying the VFOA of a person is challenging since it changes rapidly in dynamic discussions. We propose ICAF (Iterative Collective Attention Focus), a system that simultaneously tracks the VFOA and speaking probabilities of all people. In order to apply the system previously unseen videos, we propose a lightly supervised technique to train the model in ICAF with performance which is only slightly worse than in the fully supervised case. Our system can visualize the predicted VFOA and speaking probabilities and interaction networks in videos.

This chapter begins with a case study of Strava, a fitness app that inadvertently exposed sensitive military information even while protecting individual users' information privacy. The case study is analyzed as an example of how recent advances in algorithmic group inference technologies threaten privacy, both for individuals and for groups. It then argues that while individual privacy from big data analytics is well understood, group privacy is not. Results of an experiment to better understand group privacy are presented. Findings show that group and individual privacy are psychologically distinct and uniquely affect people's evaluations, use, and tolerance for a fictitious fitness app. The chapter concludes with a discussion of group-inference technologies ethics and offers recommendations for fitness app designers.

Written by Michelle A. Amazeen, Fabrício Benevenuto, Nadia M. Brashier, Robert M. Bond, Lia C. Bozarth, Ceren Budak, Ullrich K. H. Ecker, Lisa K. Fazio, Emilio Ferrara, Andrew J. Flanagin, Ales-sandro Flammini, Deen Freelon, Nir Grinberg, Ralph Hertwig, Kathleen Hall Jamieson, Kenneth Jo-seph, Jason J. Jones, R. Kelly Garrett, Daniel Kreiss, Shannon McGregor, Jasmine McNealy, Drew Margolin, Alice Marwick, FiIippo Menczer, Miriam J. Metzger, Seungahn Nah, Stephan Lewan-dowsky, Philipp Lorenz-Spreen, Pablo Ortellado, Irene Pasquetto, Gordon Pennycook, Ethan Porter, David G. Rand, Ronald Robertson, Briony Swire-Thompson, Francesca Tripodi, Soroush Vosoughi, Chris Vargo, Onur Varol, Brian E. Weeks, John Wihbey, Thomas J. Wood, & Kai-Cheng Yang

An experiment using a representative sample of US. Internet users in the context of online encyclopedias is conducted to understand how the type of information source (expert-generated, user-genera...

Biases in language influence how we interact with each other and society at large. Language affirming gender stereotypes is often observed in various contexts today, from recommendation letters and Wikipedia entries to fiction novels and movie dialogue. Yet to date, there is little agreement on the methodology to quantify gender stereotypes in natural language (specifically the English language). Common methodology (including those adopted by companies tasked with detecting gender bias) rely on a lexicon approach largely based on the original BSRI study from 1974. In this paper, we reexamine the role of gender stereotype detection in the context of modern tools, by comparatively analyzing efficacy of lexicon-based approaches and end-to-end, ML-based approaches prevalent in state-of-the-art natural language processing systems. Our efforts using a large dataset show that even compared to an updated lexicon-based approach, end-to-end classification approaches are significantly more robust and accurate, even when trained by moderately sized corpora.

Online social networks are major hubs of communications that are used to share information by societies worldwide. However, the ability to freely communicate on these platforms is increasingly restricted in countries across the globe and existing technological solutions do not fully address the needs of affected communities. In this paper we explore the design process of SecurePost, a novel tool that allows verified group anonymity to those communicating publicly on online social networks. We present survey-based research and ethnographic interviews of communities vulnerable to censorship conducted in Zambia, Turkey, and Mongolia between 2013 to 2016. We use analysis of this data to ground our work. We explore needs and requirements of users such as modes of censorship, resistance to network disruption, and appropriate platform consideration. We outline our technological solution and expand on how on-the-ground research of user communities guides technological requirements.

Machine learning and data mining threaten personal privacy, and many tools exist to help users protect their privacy (e.g., available privacy settings on Facebook, anonymization and encryption of personal data, etc.). But such technologies also pose threats to "group privacy," which is a concept scholars know relatively little about. Moreover, there are few tools to address the problem of protecting group privacy. This paper discusses an emerging class of software applications and services that pose new risks to group privacy by revealing group-level information based on individual information, such as social media postings or fitness app usage. The paper describes the results of two experiments that empirically establish the concept of group privacy and shows that it affects user perceptions of and interactions with information technology. The findings serve as a call to developers to design tools for group privacy protection.

For millions of workers, online job listings provide the first point of contact to potential employers. As a result, job listings and their word choices can significantly affect the makeup of the responding applicant pool. Here, we study the effects of potentially gender-biased terminology in job listings, and their impact on job applicants, using a large historical corpus of 17 million listings on LinkedIn spanning 10 years. We develop algorithms to detect and quantify gender bias, validate them using external tools, and use them to quantify job listing bias over time. We then perform a user survey over two user populations (N 1=469 , N 2=273 ) to validate our findings and to quantify the end-to-end impact of such bias on applicant decisions. Our findings show gender-bias has decreased significantly over the last 10 years. More surprisingly, we find that impact of gender bias in listings is dwarfed by our respondents' inherent bias towards specific job types.

Today, the internet serves a wealth of news sources that encourages selective exposure to attitude-consistent and likeminded information. Several cues have been proposed to influence selective exposure, including partisanship, familiarity, and differential framing techniques. This study investigates the effects of news brand partisanship and news lead partisanship on selective exposure behaviors to internet news stories. With online news, it is possible that news brands believed to have a particular partisan bias may feature stories with an opposite partisan bias. This paper asks which of the two tested selective exposure cues used in this study participants respond to in an online news search environment. Using a non-college adult sample of 382 participants, this study confirms that selective exposure behavior is robust in a simulated news search environment and that news brand partisanship is a more powerful predictor of exposure than is news lead partisanship. The study finds, however, that the news br...

Comparatively optimistic people feel that they are less susceptible to risks than are others. This study investigated predictors and outcomes of comparative optimism about privacy risks on Facebook. Results from a nationally representative survey of adult U.S. Facebook users (N = 1,156) show that users exhibit comparative optimism in believing that they are less susceptible to privacy risks than are average users. However, unlike prior findings in offline contexts, this study finds that comparatively optimistic Facebook users do not appear to engage in riskier privacy behaviors. The findings of this study shed light on how privacy decision-making may be different in social networking contexts compared to other contexts due to the networked nature of the communication platform.

Fake news emerged as an apparent global problem during the 2016 U.S. Presidential election. Addressing it requires a multidisciplinary effort to define the nature and extent of the problem, detect fake news in real time, and mitigate its potentially harmful effects. This will require a better understanding of how the Internet spreads content, how people process news, and how the two interact. We review the state of knowledge in these areas and discuss two broad potential mitigation strategies: better enabling individuals to identify fake news, and intervention within the platforms to reduce the attention given to fake news. The cooperation of Internet platforms (especially Facebook, Google, and Twitter) with researchers will be critical to understanding the scale of the issue and the effectiveness of possible interventions., This is the accepted version of the article, posted to comply with public access mandates. The final published version is available at https://doi.org/10.1126/science.aao2998

Visual focus of attention in multi-person discussions is a crucial nonverbal indicator in tasks such as inter-personal relation inference, speech transcription, and deception detection. However, predicting the focus of attention remains a challenge because the focus changes rapidly, the discussions are highly dynamic, and the people's behaviors are inter-dependent. Here we propose ICAF (Iterative Collective Attention Focus), a collective classification model to jointly learn the visual focus of attention of all people. Every person is modeled using a separate classifier. ICAF models the people collectively---the predictions of all other people's classifiers are used as inputs to each person's classifier. This explicitly incorporates inter-dependencies between all people's behaviors. We evaluate ICAF on a novel dataset of 5 videos (35 people, 109 minutes, 7604 labels in all) of the popular Resistance game and a widely-studied meeting dataset with supervised prediction. See our demo at https://cs.dartmouth.edu/dsail/demos/icaf. ICAF outperforms the strongest baseline by 1%--5% accuracy in predicting the people's visual focus of attention. Further, we propose a lightly supervised technique to train models in the absence of training labels. We show that light-supervised ICAF performs similar to the supervised ICAF, thus showing its effectiveness and generality to previously unseen videos.

The privacy calculus established that online self-disclosures are based on a cost-benefit tradeoff. For the context of SNSs, however, the privacy calculus still needs further support as most studies consist of small student samples and analyze self-disclosure only, excluding self-withdrawal e.g., the deletion of posts, which is essential in SNS contexts. Thus, this study used a U.S. representative sample to test the privacy calculus' generalizability and extend its theoretical framework by including both self-withdrawal behaviors and privacy self-efficacy. Results confirmed the extended privacy calculus model. Moreover, both privacy concerns and privacy self-efficacy positively predicted use of self-withdrawal. With regard to predicting self-disclosure in SNSs, benefits outweighed privacy concerns; regarding self-withdrawal, privacy concerns outweighed both privacy self-efficacy and benefits.

This study investigated the effects of message and social cues on selective exposure to political information in a social media environment. Based on the heuristic-systematic model, we hypothesized that readers' selective consideration of specific cues can be explained by situational motivations. In an experiment (N = 137), subjects primed with motivational goals (accuracy, defense, or impression motivations, as well as a control group) were asked to search for information. Participants preferred attitude-consistent information and balanced information over attitude-inconsistent information, and also preferred highly recommended articles. Defense-motivated partisans exhibited a stronger confirmation bias, whereas impression motivation amplified the effects of social recommendations. These findings specify the conditions under which individuals engage in narrow, open-minded, or social patterns of information selection.

Older adults can form parasocial relationships with favorite television characters, and these relationships often serve as sources of companionship. Using the selection, optimization, and compensation model as a guiding framework, this study explored whether or not attachment anxiety and relationship quality with romantic partners and children moderate the associations between parasocial relationships and depressive symptoms. A series of three-way interactions emerged in predicting depressive symptoms. Among other findings, stronger parasocial relationships predicted an increase in depressive symptoms for anxious older adults in low-quality parent-child relationships. Older adults' individual characteristics and family relationships may qualify how they experience parasocial relationships with favorite television characters.

The perceived credibility of information plays a major role in information selection and influence (Metzger & Flanagin, 2015). Accordingly, past research has examined people's information selection and their decision outcomes, in both web and social media environments (e.g., Knobloch-Westerwick, 2015; Winter & Kramer, 2012). Yet, in spite of this research, the specific processes of people's information selection and credibility assessment are not fully understood. To better specify credibility evaluation behaviors, we employed eye-tracking methods as a means to determine precisely which web page cues (i.e., author, introduction, short advance summary, social media information, pro & con arguments, peer comments, poll on the topic) people attend to as they form opinions about web site credibility. Additionally, we induced participants' information search motivations (i.e., accuracy, defense, impression motivation, or a control). 87 participants in our study viewed a web page for 3.5 minutes while their eye movements were tracked. Think-aloud techniques and post-hoc credibility ratings were used to assess their approaches. Surprisingly, although author information has been shown to have an important impact on both selection and credibility assessment (Winter & Kramer, 2012), results showed that it is consulted last. Primary attention is given to arguments on the web page, and the introduction and short advance summary. Social information appears to be less relevant. Moreover, there is no correlation between duration of browsing various cues and credibility assessment. Also, the patterns of observation are not dependent on information search motivations.

Selective exposure research indicates that news consumers tend to seek out attitude-consistent information and avoid attitude-challenging information. This study examines online news credibility and cognitive dissonance as theoretical explanations for partisan selective exposure behavior. After viewing an attitudinally consistent, challenging, or politically balanced online news source, cognitive dissonance, credibility perceptions, and likelihood of selective exposure were measured. Results showed that people judge attitude-consistent and neutral news sources as more credible than attitude-challenging news sources, and although people experience slightly more cognitive dissonance when exposed to attitude-challenging news sources, overall dissonance levels were quite low. These results refute the cognitive dissonance explanation for selective exposure and suggest a new explanation that is based on credibility perceptions rather than psychological discomfort with attitude-challenging information.

Taking the logic of online connective action from an information-processing viewpoint, an online experiment ( N = 208) was done to examine whether individuals’ cognitive elaboration on messages received from different sources (personal: friends, family, vs. impersonal: organization) mediates their willingness to engage in connective-type collective activities on social media (e.g., commenting, “Liking”); and whether this indirect influence is biased by perceived source credibility. Results revealed significant influence from personal sources. Cognitive elaboration positively mediates this influence and was conditionally affected by high source credibility. Direct influence from personal issue involvement and perceived self and technological efficacy was also observed. Theoretical contributions (i.e., cognitive demands at individual level) and practical implications (i.e., enhancing organizational credibility, popularity of easy-to-do acts) are discussed.

This study investigates comparative optimism—whereby people perceive themselves as relatively invulnerable to risks as compared to others—in the evaluation of online information credibility by children and their parents. Results of a representative national survey of Internet users revealed significant antecedents of children's and parents' comparative optimism, including demographic characteristics, cognitive thinking style, and perceived self-efficacy. Parental optimism was also found to relate to the mediation strategies used to regulate children's Internet use, and comparative optimism in children was associated with tendencies to believe online information and specific evaluation behavior. Findings are considered in terms of their theoretical implications and with regard to the role of parents in children's digital information literacy development.

Young people are increasingly turning to the Internet more than to traditional media and information sources to find information. Yet, research demonstrates suboptimal online information literacy among youth today, suggesting potential shortcomings in young people's information consumption behaviors. To assess this, this study investigates several predictors of young people's success in online information evaluation, including their awareness of credibility problems associated with digital information, their use of specific information evaluation practices, and their accuracy in credibility assessment. Results from a study of 2,747 11–18-year-old Internet users indicate both expected and surprising influences of young people's cognitive development, decision-making style, demographic background, and digital information literacy training on their information evaluation awareness, skills, and practices. Theoretical implications and those for redesigning online information literacy interventions are discussed.

This entry provides an overview of research findings and theories regarding trust and privacy in electronic commerce. Trust and privacy are particularly important in the area of e-commerce given the considerable risk associated with the commercialization of products and services via the internet and mobile technology. The entry reviews key concepts from the trust and privacy literature, including the antecedents and outcomes of e-commerce trust, the impact of privacy concern on consumer behaviors, and privacy policies and regulations. Keywords: consumer behavior; e-commerce; internet; mobile communication; privacy; risk; trust

As networked information and communication technologies have enabled nearly instant access, from virtually anywhere, to almost inconceivably large information repositories, people have come to rely upon web-based information resources in a wide variety of ways. For example, even as early as 2006, nearly half of users in the United States said that the Internet played a crucial or important role in at least one major decision in their lives, such as attaining additional career training, helping themselves or someone else with a major illness or medical condition, or making a major investment or financial decision (Horrigan & Rainie, 2006). Yet, the credibility of information obtained online can be problematic, which raises concerns about how people obtain, interpret, and evaluate this information.

Our understanding and perceptions of source credibility significantly drive how we process health and risk messages, and may also influence relevant behaviors. Source credibility is believed to be impacted by both perceptions of source trustworthiness and expertise, and the effect of credibility on changes in attitudes and behavior has been studied for decades in the persuasion literature. However, how we understand and define source credibility—particularly the dimension of expertise—has changed dramatically as social media and other online platforms are increasingly used to design and disseminate health messages. While earlier definitions of source credibility relied heavily on the source’s credentials as indicators of expertise on a given topic, more recent conceptualizations must also account for expertise held by laypeople who have experience with a health concern. This shifting conceptualization of source credibility may then impact both why and when people select, as well as how they perceive, process, and judge, health messaging across both novel and more traditional communication contexts.

We introduce the concept of social media self-efficacy (SMSE).We examine this concept using survey data (N=3568) of Internet users.Users with higher SMSE find online social information to be more trustworthy.They also use others' opinions and social media when evaluating information. This study introduces the concept of social media self-efficacy, or a person's perceived ability to reach desired outcomes in the social media environment, and examines the relationship between social media self-efficacy and how people evaluate information found online. Results of a survey of a representative sample of adult Internet users in the United States (N=3568) indicate that users with higher social media self-efficacy find information shared via social media to be more trustworthy than do those lower in social media self-efficacy. These self-efficacious social media users also rely more both on the opinions of others and on social media specifically when evaluating or verifying the information they find online, suggesting that they may be more prone to seek out and be influenced by input from others. Practical and theoretical implications of these findings are explored.

© 2014, Springer Science+Business Media Dordrecht.Proficiency in digital literacy refers to the ability to read and write using online sources, and includes the ability to select sources relevant to the task, synthesize information into a coherent message, and communicate the message with an audience. The present study examines the determinants of digital literacy proficiency by asking 150 students who had 50 min of access to the Internet and a word processor to produce a research report on whether or not their college should require all students to own a laptop computer. The resulting essay received a holistic rating from 1 to 5. Concerning knowledge underlying digital literacy, the major predictors of digital literacy proficiency (as measured by essay rating) were academic experience (undergraduate versus graduate status) and domain knowledge (based on a questionnaire), rather than technical knowledge about how to use computers (based on a questionnaire). Concerning processing during the task, the major predictors of digital literacy proficiency were integrating processes (such as number of unique sources, citations, or supporting details) rather than search processes (such as number of actions, web pages, websites, links, or search terms). In short, proficiency in digital literacy depended mainly on academic experience rather than technical experience, and on how learners organize and integrate the information they find rather than on how much information they peruse. Findings from this study suggest that the basic tenets of good scholarship apply to digital media.

This panel addresses information credibility issues in the context of social media. During this panel, participants will discuss people's credibility perceptions of online content in social media f ...

Networked digital media present new challenges for people to locate information that they can trust. At the same time, societal reliance on information that is available solely or primarily via the Internet is increasing. This article discusses how and why digitally networked communication environments alter traditional notions of trust, and presents research that examines how information consumers make judgments about the credibility and accuracy of information they encounter online. Based on this research, the article focuses on the use of cognitive heuristics in credibility evaluation. Findings from recent studies are used to illustrate the types of cognitive heuristics that information consumers employ when determining what sources and information to trust online. The article concludes with an agenda for future research that is needed to better understand the role and influence of cognitive heuristics in credibility evaluation in computer-mediated communication contexts.

The warranting principle, signaling theory, and theories of informational social influence suggest conditions when either user-generated information, or information originating from traditional experts, might be privileged online. A random sample of 1207 U.S.-based adults with Internet access completed an experiment that manipulated the source, volume, and valence of online movie ratings in order to test predictions derived from these perspectives. Results indicated that ratings volume is positively associated with trust of, reliance on, and confidence in user-generated content, as well as the congruence between one's own and others' opinions; that ratings source and volume interact to impact credibility perceptions, reliance on user-generated information, and opinion congruence, such that people tend to favor experts when there is low information volume, but favor user-generated information under conditions of high information volume; and that people's opinions and behavioral intentions converge with the online ratings information to which they are exposed. In addition, these effects apply more strongly to people more conversant with user-generated content. Results indicate important theoretical extensions by demonstrating that social information online may be filtered through signals indicating its veracity, which may not apply equally to all social media users.

Using Shrum's (1996) heuristic processing model as an explanatory mechanism, we propose that people who hold vivid autobiographical memories for a specific past experience with media violence will overstate the prevalence of real-world crime versus individuals without vivid memories. We also explore the effects of frequency and recency on social reality beliefs. A survey was administered to 207 undergraduate students who were asked to recall one violent television program or movie seen in the past. Participants were asked to write essays describing the violence, which were coded for vividness. Results support not only cultivation theory, but also the effects of memory vividness: participants with more vivid memories of blood and gore gave higher prevalence estimates of real-world crime and violence than participants with less vivid memories. Findings also suggest that females had more vivid memories for prior media violence than males. Implications for cultivation, the heuristic processing model, and vivi...