Sonja Utz

The function of self-disclosure on social network sites

Three alternative models how updates on Facebook create closeness are tested.The more intimate communication on Facebook is hidden in private conversations.Here, the classical link between intimacy and feeling of connection holds.Positive and entertaining updates also increase the feeling of connection.Interaction partner responsiveness plays no significant role on social media. How can social network sites (SNS) foster relationships when most status updates on SNS are mainly entertaining and not very intimate? This finding cannot be explained by classical social psychological theories such as social penetration theory which regard disclosure intimacy as the main driver of relational outcomes. By building on literature on the role of capitalization and humor in relationship formation and maintenance, this paper suggests two alternative paths from public self-disclosure to relational outcomes. Respondents judged the content and relational effects of own and friends status updates as well as private conversations. In general, all types of messages were mainly positive and entertaining. The more intimate communication took place in private conversations; here, the classical link between disclosure intimacy and feeling connected still held. However, positive and entertaining self-disclosures also increased the feeling of connection, especially when reading friends updates. Interestingly, interaction partners responsiveness did not play a significant role, indicating that results from dyadic face-to-face interactions do not hold for public communication on social media. The study contributes to the development of a more differentiated model on the role of self-disclosure on SNS.

The emotional responses of browsing Facebook

Highlights • Positive emotions are more prevalent than negative emotions while browsing Facebook.• Users are happier when a positive post comes from a strong tie rather than a weak tie.• Similarly, users experience more benign envy when a post comes from a strong tie.• The experience of malicious envy is independent of tie strength.

Types of deception and underlying motivation: what people think

In computer-mediated communication, there are various types of possible deception such as category deception (gender switching), attractiveness deception, or identity concealment. The present article argues that it is meaningful to differentiate among these types of deception. More specifically, it is assumed that people attribute the various types of deception to different motivations and that these assumed motivations determine the evaluation of the deception. To examine whether individuals indeed attribute different types of deception to different underlying motivations, a scenario study was conducted. The results were in line with the expectations. For example, identity concealment was mainly attributed to privacy concerns, whereas gender switchingwas mainly perceived as playing with newroles and unknownaspects of the self. The assumed malicious intention predicted the evaluation of the deception.

Distributive Justice in Common-Bond and Common-Identity Groups

Two experiments tested whether common-bond groups (attachment based on interpersonal bonds between the members) and common-identity groups (attachment based on attraction to the group as a whole; Prentice, Miller, & Lightdale, 1994) make different fairness judgments. Overall, the use of the equality heuristic (Messick, 1993) was expected. Moreover, based on social identity theory, we predicted that members of common-bond groups show an egocentric bias, whereas members of common-identity groups forgo their individual goals for the group goal. In both experiments, positive and negative outcomes were distributed. Experiment 1 manipulated the degree of involvement, Experiment 2 varied responsibility for the outcome. Results of both studies supported the hypothesis, thus emphasizing the importance of the distinction between common-bond and common-identity groups.

'Egoboo' vs. altruism: the role of reputation in online consumer communities

This article focuses on the role of reputation in consumer communities. Reputation systems can have a sanctioning function (incentive for good conduct) or a signalling function (e.g. signalling competence or trustworthiness). If the sanctioning function is dominant, striving for reputation should be the major motivation for contribution. However, contributions also can be motivated by altruism, the pleasure of interaction, earning money or generalized reciprocity. An online study of members of a German consumer community assessed the motivations for contribution and the evaluation of various features of the site. Overall, reputation turned out to be the least important motivation. Five types of users could be distinguished, but only the multiple motive consumers scored high on reputation. However, all community members perceived the quality ratings of the reviews as very important. The findings suggest that reputation has mainly a signalling function, but not so much of a sanctioning function in consumer communities.

Is LinkedIn making you more successful? The informational benefits derived from public social media

This article uses a social capital framework to examine whether and how the use of three types of publicly accessible social media (LinkedIn, Twitter, Facebook) is related to professional informational benefits among a representative sample of Dutch online users. Professional informational benefits were conceptualized as the (timely) access to relevant information and being referred to career opportunities. The effect of content and structure of the respective online network on professional informational benefits was examined on the general (users vs. non-users of a platform) and more fine-grained level (within users of a specific platform). Overall, users of LinkedIn and Twitter reported higher informational benefits than non-users, whereas the Facebook users reported lower informational benefits. Posting about work and strategically selecting ties consistently predicted informational benefits. The network composition mattered most on LinkedIn; strong and weak ties predicted informational benefits. The results demonstrate the usefulness of the social capital framework.

Knowledge acquisition from social platforms based on network distributions fitting

New approach to knowledge acquisition based on social network distributions.Increased the representativeness of samples using distance from distributions.Applications in the area of collaborative learning and knowledge diffusion.Improved adaptive selection processes based on given characteristics.New algorithms following presented approach can be implemented. The uniqueness of online social networks makes it possible to implement new methods that increase the quality and effectiveness of research processes. While surveys are one of the most important tools for research, the representativeness of selected online samples is often a challenge and the results are hardly generalizable. An approach based on surveys with representativeness targeted at network measure distributions is proposed and analyzed in this paper. Its main goal is to focus not only on sample representativeness in terms of demographic attributes, but also to follow the measures distributions within main network. The approach presented has many application areas related to online research, sampling a network for the evaluation of collaborative learning processes, and candidate selection for training purposes with the ability to distribute information within a social network.

Making źFriendsź in a Virtual World

Graphical virtual worlds add two new layers to the old question what determines friendship formation. First, it is possible to distinguish between off-line (player) and online (avatar) characteristics. Second, these environments offer new possibilities for studying friendship formation. By tracking friendship requests and their acceptance rate, researchers are able to distinguish between with whom players want to become friends and with whom they actually do become friends. This article examined friendship formation in Timik, a graphical virtual world targeted at Polish teenagers. Homophily, preferential attachment and status were tested as possible underlying mechanisms. Results showed that preferential attachment and status drove invitations: Players wanted to become friends with high-status players. However, high-status players were also more likely to reject offers. Homophily only played a minor role. Players preferred players of the same avatar class and similar age but of the opposite sex. Too similar avatars were disliked. The results are discussed in the light of the generalizability of off-line theories of friendship formation to online worlds.

Making “Friends” in a Virtual World

Graphical virtual worlds add two new layers to the old question what determines friendship formation. First, it is possible to distinguish between off-line (player) and online (avatar) characteristics. Second, these environments offer new possibilities for studying friendship formation. By tracking friendship requests and their acceptance rate, researchers are able to distinguish between with whom players want to become friends and with whom they actually do become friends. This article examined friendship formation in Timik, a graphical virtual world targeted at Polish teenagers. Homophily, preferential attachment and status were tested as possible underlying mechanisms. Results showed that preferential attachment and status drove invitations: Players wanted to become friends with high-status players. However, high-status players were also more likely to reject offers. Homophily only played a minor role. Players preferred players of the same avatar class and similar age but of the opposite sex. Too similar avatars were disliked. The results are discussed in the light of the generalizability of off-line theories of friendship formation to online worlds.

Adaptive Survey Design Using Structural Characteristics of the Social Network

The implementation of new methods that increase the quality and effectiveness of research processes became an unique advantage to online social networking sites. Conducting accurate and meaningful surveys is one of the most important facets for research, wherein the representativeness of selected online samples is often a challenge and the results are hardly generalizable. This study presents a proposal and analysis based on surveys with representativeness targeted at network characteristics. Hence, the main goal of this study is to follow the measures’ computed for the main network during survey and focusing on acquiring similar distributions for sample.