A Review of Facebook Research in the Social Sciences

Perspectives on Psychological Science (Impact Factor: 4.89). 05/2012; 7(3):203-220. DOI: 10.1177/1745691612442904


With over 800 million active users, Facebook is changing the way hundreds of millions of people relate to one another and share information. A rapidly growing body of research has accompanied the meteoric rise of Facebook as social scientists assess the impact of Facebook on social life. In addition, researchers have recognized the utility of Facebook as a novel tool to observe behavior in a naturalistic setting, test hypotheses, and recruit participants. However, research on Facebook emanates from a wide variety of disciplines, with results being published in a broad range of journals and conference proceedings, making it difficult to keep track of various findings. And because Facebook is a relatively recent phenomenon, uncertainty still exists about the most effective ways to do Facebook research. To address these issues, the authors conducted a comprehensive literature search, identifying 412 relevant articles, which were sorted into 5 categories: descriptive analysis of users, motivations for using Facebook, identity presentation, the role of Facebook in social interactions, and privacy and information disclosure. The literature review serves as the foundation from which to assess current findings and offer recommendations to the field for future research on Facebook and online social networks more broadly.
© The Author(s) 2012.

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    • "Therefore, in this research profile disclosure is examined to understand its antecedents so that individuals can still safety disclose information without the possibility of a privacy breach, and so that businesses can understand what is important to users in order to allay their fears. Much of the research in this realm is survey based and has been studying user behaviour in order to catalogue privacy, disclosure, user motivations, as well as, their impacts on relationships (Wilson et al., 2012). Some theories that have been used to explain information privacy and disclosure include privacy calculus, expectancy value theories, and social contact theories (see Li (2012) for a review). "
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    ABSTRACT: The magnitude of information shared on online social networks (OSN), such as Facebook, and their exponential growth brings to light the importance of understanding individual’s profile disclosure. Encouraging disclosure is crucial for OSN to succeed as a business model, i.e., by using OSN as an advertising platform. A model was built making use of the theory of planned behaviour (TPB) augmented by the ABC model of attitude, to investigate the affective, behavioural, and cognitive antecedents to attitude. To validate the model a survey was conducted, and the results were analysed with SmartPLS. Privacy risk, benefits, OSN trust, interpersonal trust, and OSN use were all found to significantly impact attitude, while attitude, social influence, and control all significantly impact profile disclosure. This research successfully applies TPB, and shows the value of including affective, behaviour, and cognitive antecedents in the OSN context. It also uniquely operationalises benefits, as well as, trust.
    International Journal of Electronic Business 12/2015; 12(2):162-184. DOI:10.1504/IJEB.2015.069106
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    • "For this reason, this research has an important pedagogical valence. As noted by Wilson and collaborators [17], Facebook data analysis has been underestimated in the field of psychology in general, and in identity research in particular. This study uses a unique method to gather and analyze data, one which is a combination of recruited volunteers' friends' FSU analysis and automated analysis of said posts. "
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    ABSTRACT: The key element of Facebook social network platform is the status updates, in which the user can upload text or other media such as pictures and videos. In this study, we manually classified more than 3500 Facebook status updates (FSUs) by the subject, the emotional activation, the medium used, the originality and the self-centeredness. We then cross-tabulated that information with demographic factors such as gender and occupation. Thirty students participated in the categorization task, each annotating more than 100 FSUs of their Facebook friends’ FSUs. Statistical and supervised machine learning analysis was then applied to the categorized features. The text itself was not analyzed further after the annotation for the purpose of preserving the privacy and anonymity of the FSU authors. Results show that FSUs vary in subject, emotional connotation and structure as a function of demographic factors like gender and occupation of the poster. Statistical analysis and supervised machine learning are able to predict the demographic and emotional expressions based on the other features annotated by the participants.
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    • "A growing body of the literature also demonstrates that SNSs can influence how individuals form impressions of others (for an overview, see Wilson et al., 2012). For example, information on a person's Facebook profile, such as the number of " friends, " can influence how users evaluate that person (e.g., Tong et al., 2008). "
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    ABSTRACT: Voters and political candidates increasingly use social networking sites (SNSs) such as Facebook. This study uses data from an online posttest-only experiment ( N = 183) in analyzing how exposure to supportive or challenging user comments on a fictional candidate's Facebook page influenced participants’ perceptions of and willingness to vote for the candidate, as well as whether candidate replies to each type of user comments affected these outcomes. Participants who viewed a page with supportive comments and “likes” reported more favorable perceptions of and greater support for the candidate, relative to participants who viewed a page with challenging comments. Thus, the appearance of interactivity between a candidate and other users on the candidate's Facebook page can shape the responses of those viewing the page. However, exposure to candidate replies to either supportive or challenging comments did not lead to significantly more favorable perceptions or a greater likelihood of voting for the candidate.
    07/2015; DOI:10.1017/XPS.2014.29
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