Based on Moral Foundations Theory used to understand ideological conflict, we found pro-immigration tweets to contain more language associated with moral foundations of harm, fairness, and loyalty. In total, we analyzed and compared the language of 45,045 pro-immigration tweets and 11,213 anti-immigration tweets spread across this period. In this work, we examine Twitter data to understand the moral, affective, and cognitive differences in language use between two opposing sides of the political debate over immigration related issues in the United States in the year since the 2016 presidential election. More specifically, understanding ideological conflict is important for studying social media platforms like Twitter, which provide the ability for people to freely express their thoughts and opinions on contentious political events. Understanding ideological conflict has been a topic of interest in CSCW, for example in Value Sensitive Design research. Despite its shortcoming in accounting for the rhetorical techniques ingrained in natural human language, the STED could be instrumental for social scientific inquiry of positive emotions in textual narratives. Results indicated that the final dictionary, consisting of 351 lexicons and phrases, exhibits acceptable face and construct validity, and possesses a reasonable level of external validity and applicability. Finally, the refined dictionary was applied to examine words used in nearly 4,000 human-coded New York Times articles (Step 3). This dictionary tool was then refined and validated via three studies, where individual words were first rated with regard to their fitness into the proposed construct (Step 1), and then used to analyze essays written to reflect the corresponding construct (Step 2).
Twitter mujeres hombres y viceversa software#
Drawing upon the word-counting approach of the text analysis paradigm, this project aimed at constructing a dictionary tool-Self-Transcendent Emotion Dictionary (STED)-which can be uploaded into mainstream, text analytic software (e.g., LIWC) to identify and analyze self-transcendent emotions in large corpora. While these emotions are invaluable to promote greater human connectedness, prosociality, and human flourishing, researchers are constrained in terms of analyzing self-transcendent emotions as expressed in spoken and written languages.
Recent years have seen a growing amount of research effort directed toward what positive media psychologists refer to as self-transcendent emotions, such as awe, admiration, elevation, gratitude, inspiration, and hope.
Twitter mujeres hombres y viceversa tv#
We conclude that social TV analysis offers a promising new way for researchers to explore issues of morality and media reception. Specifically, we observed and discussed the importance of tweets (a) reflecting language from five moral domains, (b) for a beloved character who suffers pain and loss, and (c) about a character who regularly violates moral norms. Based on moral foundation theory and affective disposition theory, we derived and examined a set of propositions.
The case study examined if, and if so how, viewers used Twitter to express their moral thoughts during the Season 3 finale of Downton Abbey. Our broad goal was to explore a potentially new methodological approach to the study of morality and media and to offer an initial case study in applying that approach. In this study, we propose that the massive, unsolicited, real-time data generated by social media might provide media psychologists with new paths for examining the role that morality and moral thinking play during the consumption of entertainment.
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