Synchronized verbal behavior can reveal important information about social dynamics. This study introduces the linguistic style matching (LSM) algorithm for calculating verbal mimicry based on an automated textual analysis of function words. The LSM algorithm was applied to language generated during a small group discussion in which 70 groups comprised of 324 individuals engaged in an information search task either face-to-face or via text-based computer-mediated communication. As a metric, LSM predicted the cohesiveness of groups in both communication environments, and it predicted task performance in face-to-face groups. Other language features were also related to the groups’ cohesiveness and performance, including word count, pronoun patterns, and verb tense. The results reveal that this type of automated measure of verbal mimicry can be an objective, efficient, and unobtrusive tool for predicting underlying social dynamics. In total, the study demonstrates the effectiveness of using language to predict change in social psychological factors of interest.
Contrasting hypotheses were posed to test the effect of Facebook exposure on self-esteem. Objective Self-Awareness (OSA) from social psychology and the Hyperpersonal Model from computer-mediated communication were used to argue that Facebook would either diminish or enhance self-esteem respectively. The results revealed that, in contrast to previous work on OSA, becoming self-aware by viewing one's own Facebook profile enhances self-esteem rather than diminishes it. Participants that updated their profiles and viewed their own profiles during the experiment also reported greater self-esteem, which lends additional support to the Hyperpersonal Model. These findings suggest that selective self-presentation in digital media, which leads to intensified relationship formation, also influences impressions of the self.
As US Internet penetration rates have climbed, digital divide researchers have largely shifted attention to differences in Internet skills. Interviews with 72 low-income US residents from both a large metropolitan city and a medium-sized Midwestern town, however, reveal that many people still struggle to maintain physical access, supporting technology maintenance theory. Technology maintenance theory argues that although most of the US poor now use digital technology, access is unstable and characterized by frequent periods of disconnection. As a result, low-income users must work to maintain access, often experiencing cycles of dependable instability. In these interviews, nearly all used the Internet, but technology maintenance practices were widespread, including negotiation of temporarily disconnected service, broken hardware, and logistic limitations on public access. As a result, participants had limited access to health information and employment, and biased attitudes toward technology. That is, in some cases, negative attitudes toward Internet adoption reflected a rational response to disconnection rather than cultural norms or fears of the Internet, as suggested by previous research. Findings support and extend the theory of technology maintenance by emphasizing a shift in the US digital divide from issues of ownership to issues of sustainability; they also provide insight into the interrelated nature of access and attitudes toward technology. This new theoretical approach complements other theoretical approaches to the digital divide that foreground a contextualized understanding of digital disparities as embedded within a history of broad social disparities.
Background Financial incentives and peer networks could be delivered through eHealth technologies to encourage older adults to walk more. Methods We conducted a 24-week randomized trial in which 92 older adults with a computer and internet access received a pedometer, daily walking goals, and weekly feedback on goal achievement. Participants were randomized to weekly feedback only (Comparison), entry into a lottery with potential to earn up to $200 each week walking goals were met (Financial Incentive), linkage to 4 other participants through an online message board (Peer Network), or both interventions (Combined). Main outcomes were the proportion of days walking goals were met during the 16-week intervention and 8-week follow-up. We conducted a content analysis of messages posted by Peer Network and Combined arm participants. Results During the 16-week intervention, there were no differences in the proportion of days walking goals were met in the Financial Incentive (39.7%; P = 0.78), Peer Network (24.9%; P = 0.08), and Combined (36.0%; P = 0.77) arms compared to the Comparison arm (36.0%). During 8 weeks of follow-up, the proportion of days walking goals were met was lower in the Peer Network arm (18.7%; P = 0.025), but not in the Financial Incentive (29.3%; P = 0.50) or Combined (24.8%; P = 0.37) arms, relative to the Comparison arm (34.5%). Messages posted by participants focused on barriers to walking and provision of social support. Conclusions Financial incentives and peer networks delivered through eHealth technologies did not result in older adults walking more.
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