Does Organizational Messaging Make a Difference? Investigating Themes and Language Style in Twitter Discourse and Engagement by Mental Health Organizations.

The present study investigated the latent topics and language styles present in mental health organizational discourse on Twitter. The researchers sought to analyze identifying the prevalence of and language used in social support messaging in tweets about mental health care, the overarching topics regarding mental health care, and predicted that tweets with higher engagement will have increased frequency of words with positively valenced emotion and cognitive processing. A GSDMM was run to uncover latent themes that emerged in a data set of 326.9k tweets and 7.2 m words about organizational discussions of mental health. A generalized linear model using the Poisson distribution was used to assess the role of engagement, positive emotion, and cognitive processing. The study found support for both positive emotion and cognitive processing as statistically significant predictors of engagement. Directions for research include the development of health message strategies, policy needs, and online interventions.

Implications for Emotion: Using Anatomically Based Facial Coding to Compare Emoji Faces Across Platforms.

Emoji faces, which are ubiquitous in our everyday communication, are thought to resemble human faces and aid emotional communication. Yet, few studies examine whether emojis are perceived as a particular emotion and whether that perception changes based on rendering differences across electronic platforms. The current paper draws upon emotion theory to evaluate whether emoji faces depict anatomical differences that are proposed to differentiate human depictions of emotion (hereafter, "facial expressions"). We modified the existing Facial Action Coding System (FACS) (Ekman and Rosenberg, 1997) to apply to emoji faces. An equivalent "emoji FACS" rubric allowed us to evaluate two important questions: First, Anatomically, does the same emoji face "look" the same across platforms and versions? Second, Do emoji faces perceived as a particular emotion category resemble the proposed human facial expression for that emotion? To answer these questions, we compared the anatomically based codes for 31 emoji faces across three platforms and two version updates. We then compared those codes to the proposed human facial expression prototype for the emotion perceived within the emoji face. Overall, emoji faces across platforms and versions were not anatomically equivalent. Moreover, the majority of emoji faces did not conform to human facial expressions for an emotion, although the basic anatomical codes were shared among human and emoji faces. Some emotion categories were better predicted by the assortment of anatomical codes than others, with some individual differences among platforms. We discuss theories of emotion that help explain how emoji faces are perceived as an emotion, even when anatomical differences are not always consistent or specific to an emotion.

What Color Is Your Anger? Assessing Color-Emotion Pairings in English Speakers.

Do English-speakers think about anger as "red" and sadness as "blue"? Some theories of emotion suggests that color(s)-like other biologically-derived signals- should be reliably paired with an emotion, and that colors should differentiate across emotions. We assessed consistency and specificity for color-emotion pairings among English-speaking adults. In study 1, participants (n = 73) completed an online survey in which they could select up to three colors from 23 colored swatches (varying hue, saturation, and light) for each of ten emotion words. In study 2, different participants (n = 52) completed a similar online survey except that we added additional emotions and colors (which better sampled color space). Participants in both studies indicated the strength of the relationship between a selected color(s) and the emotion. In study 1, four of the ten emotions showed consistency, and about one-third of the colors showed specificity, yet agreement was low-to-moderate among raters even in these cases. When we resampled our data, however, none of these effects were likely to replicate with statistical confidence. In study 2, only two of 20 emotions showed consistency, and three colors showed specificity. As with the first study, no color-emotion pairings were both specific and consistent. In addition, in study 2, we found that saturation and lightness, and to a lesser extent hue, predicted color-emotion agreement rather than perceived color. The results suggest that previous studies which report emotion-color pairings are likely best thought of experiment-specific. The results are discussed with respect to constructionist theories of emotion.