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From Insult to Hate Speech: Mapping Offensive Language in German User Comments on Immigration
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In: Media and Communication ; 9 ; 1 ; 171-180 ; Dark Participation in Online Communication: The World of the Wicked Web (2021)
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Us vs. Them as Structural Equivalence: Analysing Nationalist Discourse Networks in the Georgian Print Media
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In: Politics and Governance ; 8 ; 2 ; 243-256 ; Policy Debates and Discourse Network Analysis (2021)
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Discourse Networks and Dual Screening: Analyzing Roles, Content and Motivations in Political Twitter Conversations
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In: Politics and Governance ; 8 ; 2 ; 311-325 ; Policy Debates and Discourse Network Analysis (2021)
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Integrating Manual and Automatic Annotation for the Creation of Discourse Network Data Sets
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In: Politics and Governance ; 8 ; 2 ; 326-339 ; Policy Debates and Discourse Network Analysis (2021)
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Tweeting on dementia: A snapshot of the content and sentiment of tweets associated with dementia
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In: First Monday; Volume 26, Number 6 - 7 June 2021 ; 1396-0466 (2021)
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DIGITAL SITES OF PROTEST: FARMERS’ PROTEST IN INDIA AND THE CONSTRUCTION OF A COLLECTIVE IDENTITY ON FACEBOOK
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In: AoIR Selected Papers of Internet Research; 2021: AoIR2021 ; 2162-3317 (2021)
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SPACE, PLACE AND LOCATION IN SEXUAL SOCIAL MEDIA
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In: AoIR Selected Papers of Internet Research; 2021: AoIR2021 ; 2162-3317 (2021)
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FROM TOP-DOWN TO BOTTOM-UP: POLITICAL IMAGE MANAGEMENT AND THE PRESERVATION OF WHITE SUPREMACY THROUGH VISUALS AND MEMES ON SOCIAL MEDIA PLATFORMS
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In: AoIR Selected Papers of Internet Research; 2021: AoIR2021 ; 2162-3317 (2021)
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130 |
Persuasion Strategies in Misinformation-containing Weibo Posts
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Combating abuse on social media platforms using natural language processing
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132 |
Consumer Cynicism Identification for Spanish Reviews using a Spanish Transformer Model ; Identificación del cinismo del consumidor para reseñas en español utilizando un modelo de transformador español
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ASIA: Automated social identity assessment using linguistic style
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Abstract:
This is the final version. Available on open access from Springer via the DOI in this record. ; Data Availability: In the interest of open science and replicability, we provide an accessible step-by-step tutorial of how to replicate our proof-of-concept studies, which can be found on ASIA’s GitHub page (https://github.com/Identity-lab/Tutorial-on-salient-social-Identity-detection-model). The tutorial contains the Python code for preparing the datasets, and the code for training and testing the models. Data for each study, including the necessary LIWC vectors and other relevant variables for each dataset, can be found on OSF: https://osf.io/87t6h/?view_only=a1b5afe488db4014b3f21ed808bcceb9. For ethical reasons (see Step 1), the original posts cannot be shared publicly but are available upon reasonable request from the first author. ; The various group and category memberships that we hold are at the heart of who we are. They have been shown to affect our thoughts, emotions, behavior, and social relations in a variety of social contexts, and have more recently been linked to our mental and physical well-being. Questions remain, however, over the dynamics between different group memberships and the ways in which we cognitively and emotionally acquire these. In particular, current assessment methods are missing that can be applied to naturally occurring data, such as online interactions, to better understand the dynamics and impact of group memberships in naturalistic settings. To provide researchers with a method for assessing specific group memberships of interest, we have developed ASIA (Automated Social Identity Assessment), an analytical protocol that uses linguistic style indicators in text to infer which group membership is salient in a given moment, accompanied by an in-depth open-source Jupyter Notebook tutorial (https://github.com/Identity-lab/Tutorial-on-salient-social-Identity-detection-model). Here, we first discuss the challenges in the study of salient group memberships, and how ASIA can address some of these. We then demonstrate how our analytical protocol can be used to create a method for assessing which of two specific group memberships—parents and feminists—is salient using online forum data, and how the quality (validity) of the measurement and its interpretation can be tested using two further corpora as well as an experimental study. We conclude by discussing future developments in the field. ; Engineering and Physical Sciences Research Council (EPSRC)
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Keyword:
Natural language processing; Psychological assessment; Social categorization; Social identity; Social media data
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URL: http://hdl.handle.net/10871/124775 https://doi.org/10.3758/s13428-020-01511-3
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Examining the Social Media Antecedents of Racial Justice: Evidence from Twitter
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Using Instagram for language learning
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Wagner, Keith. - : University of Hawaii National Foreign Language Resource Center, 2021. : (co-sponsored by American Association of University of Supervisors and Coordinators; Center for Advanced Research on Language Acquisition; Center for Educational Reources in Culture, Language, and Literacy; Center for Open Educational Resources and Language Learning; Open Language Resource Center; Second Language Teaching and Resource Center), 2021
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Inferring the Relationship between Anxiety and Extraversion from Tweets during COVID19 – A Linguistic Analytics Approach
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Blowing the Whistle on Opioid Overprescription: Insights from Patient Feedback on Physician Rating Websites
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Unsupervised Deep Learning for Fake Content Detection in Social Media
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Content and Social Network Analyses of Depression-related Tweets of African American College Students
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