Social media emotions annotation guide (SMEmo): Development and initial validity.

The proper measurement of emotion is vital to understanding the relationship between emotional expression in social media and other factors, such as online information sharing. This work develops a standardized annotation scheme for quantifying emotions in social media using recent emotion theory and research. Human annotators assessed both social media posts and their own reactions to the posts' content on scales of 0 to 100 for each of 20 (Study 1) and 23 (Study 2) emotions. For Study 1, we analyzed English-language posts from Twitter (N = 244) and YouTube (N = 50). Associations between emotion ratings and text-based measures (LIWC, VADER, EmoLex, NRC-EIL, Emotionality) demonstrated convergent and discriminant validity. In Study 2, we tested an expanded version of the scheme in-country, in-language, on Polish (N = 3648) and Lithuanian (N = 1934) multimedia Facebook posts. While the correlations were lower than with English, patterns of convergent and discriminant validity with EmoLex and NRC-EIL still held. Coder reliability was strong across samples, with intraclass correlations of .80 or higher for 10 different emotions in Study 1 and 16 different emotions in Study 2. This research improves the measurement of emotions in social media to include more dimensions, multimedia, and context compared to prior schemes.

Emotional content and sharing on Facebook: A theory cage match.

While emotional content predicts social media post sharing, competing theories of emotion imply different predictions about how emotional content will influence the virality of social media posts. We tested and compared these theoretical frameworks. Teams of annotators assessed more than 4000 multimedia posts from Polish and Lithuanian Facebook for more than 20 emotions. We found that, drawing on semantic space theory, modeling discrete emotions independently was superior to models examining valence (positive or negative), activation/arousal (high or low), or clusters of emotions and was on par with but had more explanatory power than a seven basic emotion model. Certain discrete emotions were associated with post sharing, including both positive and negative and relatively lower and higher activation/arousal emotions (e.g., amusement, cute/kama muta, anger, and sadness) even when controlling for number of followers, time up, topic, and Facebook angry reactions. These results provide key insights into better understanding of social media post virality.

Use of the first-acquired language modulates pupil size in the processing of island constraint violations.

Introduction: Traditional studies of the population called "heritage speakers" (HS) have treated this group as distinct from other bilingual populations, e.g., simultaneous or late bilinguals (LB), focusing on group differences in the competencies of the first-acquired language or "heritage language". While several explanations have been proposed for such differences (e.g., incomplete acquisition, attrition, differential processing mechanisms), few have taken into consideration the individual variation that must occur, due to the fluctuation of factors such as exposure and use that characterize all bilinguals. In addition, few studies have used implicit measures, e.g., psychophysiological methods (ERPs; Eye-tracking), that can circumvent confounding variables such as resorting to conscious metalinguistic knowledge. Methodology: This study uses pupillometry, a method that has only recently been used in psycholinguistic studies of bilingualism, to investigate pupillary responses to three syntactic island constructions in two groups of Spanish/English bilinguals: heritage speakers and late bilinguals. Data were analyzed using generalized additive mixed effects models (GAMMs) and two models were created and compared to one another: one with group (LB/HS) and the other with groups collapsed and current and historical use of Spanish as continuous variables. Results: Results show that group-based models generally yield conflicting results while models collapsing groups and having usage as a predictor yield consistent ones. In particular, current use predicts sensitivity to L1 ungrammaticality across both HS and LB populations. We conclude that individual variation, as measured by use, is a critical factor tha must be taken into account in the description of the language competencies and processing of heritage and late bilinguals alike.

The construct of cuteness: A validity study for measuring content and evoked emotions on social media.

Social media users are often exposed to cute content that evokes emotional reactions and influences them to feel or behave certain ways. The cuteness phenomenon in social media has been scarcely studied despite its prevalence and potential to spread quickly and affect large audiences. The main framework for understanding cuteness and emotions related to cuteness outside of social media is baby schema (having juvenile characteristics), which triggers parental instincts. We propose that baby schema is a necessary but not sufficient component of explaining what constitutes cuteness and how people react to it in the social media context. Cute social media content may also have characteristics that evoke approach motivations (a desire to interact with an entity, generally with the expectation of having a positive experience) that can manifest behaviorally in sharing and other prosocial online behaviors. We developed and performed initial validation for measures in social media contexts of: (1) cute attributes that encompass both baby schema and other proposed cuteness characteristics (the Cuteness Attributes Taxonomy, CAT) and (2) the emotional reactions they trigger (Heartwarming Social Media, HSM). We used the Kama Muta Multiplex Scale (KAMMUS Two), as previously validated measure of kama muta (an emotion akin to tenderness; from Sanskrit, "moved by love") as a measure of emotional reaction to cute stimuli and the dimension Cute Content of the Social Media Emotions Annotation Guide (SMEmo-Cute Content) as a developed measure of gestalt cute content to help validate our newly developed measures. Using 1,875 Polish tweets, our results confirmed that cute social media content predicted a kama muta response, but not all KAMMUS Two subscales were sensitive to cute content, and that the HSM measure was a better indicator of the presence of cute content. Further, the CAT measure is an effective means of categorizing cute attributes of social media content. These results suggest potential differences between in-person, online, and social media experiences evoking cute emotional reactions, and the need for metrics that are developed and validated for use in social media contexts.

Performance on stochastic figure-ground perception varies with individual differences in speech-in-noise recognition and working memory capacity.

Speech recognition in noisy environments can be challenging and requires listeners to accurately segregate a target speaker from irrelevant background noise. Stochastic figure-ground (SFG) tasks in which temporally coherent inharmonic pure-tones must be identified from a background have been used to probe the non-linguistic auditory stream segregation processes important for speech-in-noise processing. However, little is known about the relationship between performance on SFG tasks and speech-in-noise tasks nor the individual differences that may modulate such relationships. In this study, 37 younger normal-hearing adults performed an SFG task with target figure chords consisting of four, six, eight, or ten temporally coherent tones amongst a background of randomly varying tones. Stimuli were designed to be spectrally and temporally flat. An increased number of temporally coherent tones resulted in higher accuracy and faster reaction times (RTs). For ten target tones, faster RTs were associated with better scores on the Quick Speech-in-Noise task. Individual differences in working memory capacity and self-reported musicianship further modulated these relationships. Overall, results demonstrate that the SFG task could serve as an assessment of auditory stream segregation accuracy and RT that is sensitive to individual differences in cognitive and auditory abilities, even among younger normal-hearing adults.

Is codeswitching easy or difficult? Testing processing cost through the prosodic structure of bilingual speech.

A common practice often attested in bilingual and multilingual communities the world over is the combination of languages within a single utterance or conversation, a practice known as codeswitching. While sociolinguistic studies of spontaneous codeswitching have demonstrated its structure and systematicity, psycholinguistic approaches have focused on the cognitive mechanisms underlying language switching, most often at the lexical level. In the present study, we seek to investigate these mechanisms using spontaneous codeswitching from an established community of Spanish-English bilinguals in northern New Mexico. Focusing on the clausal rather than the lexical level, we find that global speech rates are fastest when bilinguals codeswitch compared to speaking only one language at a time. These results point to codeswitching as a unique discourse mode that these bilinguals use to facilitate production and suggests that what may appear costly at one level may be beneficial at another.