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U.S. political party genderization (Republicans as masculine; Democrats as feminine) is well-documented in research. To determine if Hillary Clinton may have disrupted these patterns as the first female major-party presidential nominee, Reddit posts during the 2016 election campaign were analyzed. Most studies focus on professional news or candidate self-presentations concocted by image handlers. We departed from this tradition, focusing on (a) gender qualities that Redditors assign to candidates on this platform and (b) statistical tracking of these patterns over time. The results provide insight into how the electorate presented the two candidates and Donald Trump’s largely unexpected victory.

Personalization refers to the journalistic practice of including emotional case studies of ordinary people in news stories, increasing vividness and emotional charge of news and eliciting identification and empathy in news consumers. Previous research suggests that personalization of news stories increases collectivistic (compared with individualistic) causal attributions by the news audience. In response, an experiment was conducted with a week time delay between stimuli presentation and open-ended participant responses to examine the influence of news personalization on how news consumers attribute causes for social issues. Participant (N = 80) trait empathy was included as an additional factor. Findings show that participants with high trait empathy expressed a greater shift to collectivistic attribution after watching personalized news stories than participants with low trait empathy, suggesting that individual differences in trait empathy may be an important factor in how individuals construct their own understanding of social problems.

Objectives A growing body of health communication scholarship has explored the utility of social media platforms for eliciting social support, although much of this scholarship has focused on Facebook and Twitter. This study contributes to this body of research by identifying support in comments submitted to depression-related Imgur posts. Furthermore, the use of non-bona fide linguistic features (e.g. humor, sarcasm, and irony) is documented for comparison with supportive elements. Methods A content analysis was performed of 1530 comments submitted in response to 20 popular Imgur posts about depression, including the emergence of four social support types outlined by the Multi-Dimensional Support Scale—reassuring, empathic, informational, and tangible support—as well as non-bona fide features. Results Findings suggest a supportive discourse, with nearly 60% of comments containing some supportive element. Reassuring and informational support emerged most prominently (26.3% and 26.2% of comments, respectively), followed by empathic (22.9%) and tangible (0.3%) support types. Non-bona fide features manifested in 28.8% of comments. Results indicate significant covariation between non-bona fide features and support, as these infrequently co-occurred. Conclusions This study’s findings suggest that depression-related messages frequently receive support from Imgur commenters, especially reassuring and informational support. Additionally, this study provides a conceptual framework for future analyses of online social support by integrating non-bona fide communication with established support types. The results of this study could have implications for health professionals and scholars interested in the use of social media platforms such as Imgur, which serves a predominantly young male demographic, for support provision.

Background: Anonymous verbal attacks against overweight individuals on social media are common and widespread. These comments often use negative, misogynist, or derogatory words, which stigmatize the targeted individuals with obesity. These verbal attacks may cause depression in overweight individuals, which could subsequently promote unhealthy eating behavior (ie, binge eating) and further weight gain. To develop an intervention policy and strategies that tackle the anonymous, Web-based verbal attacks, a thorough understanding of the comments is necessary. Objective: This study aimed to examine how anonymous users verbally attack or defend overweight individuals in terms of 3 themes: (1) topic of verbal attack (ie, what aspects of overweight individuals are verbally attacked), (2) gender of commenters and targeted overweight individuals, and (3) intensity of derogation depending on the targeted gender (ie, the number of swear words used within comments). Methods: This study analyzed the content of YouTube comments that discuss overweight individuals or groups from 2 viral videos, titled “Fat Girl Tinder Date” and “Fat Guy Tinder Date.” The twin videos provide an avenue through which to analyze discussions of obesity as they organically occurred in a contemporary setting. We randomly sampled and analyzed 320 comments based on a coding instrument developed for this study. Results: First, there were twice as many comments verbally attacking overweight individuals (n=174) than comments defending them (n=89). Second, overweight women are attacked for their capacities (eg, laziness, maturity; 14/51, 28%), whereas overweight men are attacked for their heterosocial skills (eg, rudeness, annoyance; 24/29, 83%). Third, the majority of commenters who attacked overweight women are male (42/52, 81%). Fourth, attacking comments generated toward overweight women included more swear words (mean 0.44, SD 0.77) than those targeting men (mean 0.23, SD 0.48). Conclusions: Our data elucidate a worrying situation of frequent disinhibited aggressive messages against overweight individuals online. Importantly, the patterns of verbal aggression differ depending on the gender of the targeted overweight individuals. Thus, gender-tailored intervention strategies that specifically tackle Internet users’ verbal aggression against overweight individuals need to be developed. [Interact J Med Res 2018;7(1):e6]

A need for advanced design tools has motivated the design and development of three new concepts in device input for 3D displays: 1) a 3D sketching environment using 2D perspective input techniques, 2) B-spline approximation of free-hand curves in 3D using a 3D input device and stereoscopic 3D output and 3) an interactive cuberille sculpting environment supporting rapid presentation and modification of 3D objects.