A Framework for Generating Annotated Social Media Corpora with Demographics, Stance, Civility, and Topicality

• URL: http://arxiv.org/abs/2012.05444v1
• Date: Thu, 10 Dec 2020 04:06:25 GMT
• Title: A Framework for Generating Annotated Social Media Corpora with Demographics, Stance, Civility, and Topicality
• Authors: Shubhanshu Mishra, Daniel Collier
• Abstract summary: We introduce a framework for annotating a social media text corpora for various categories. We use a case study of a Facebook comment corpora on student loan discussion which was annotated for gender, military affiliation, age-group, political leaning, race, stance, topicalilty, neoliberlistic views and civility of the comment.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: In this paper we introduce a framework for annotating a social media text corpora for various categories. Since, social media data is generated via individuals, it is important to annotate the text for the individuals demographic attributes to enable a socio-technical analysis of the corpora. Furthermore, when analyzing a large data-set we can often annotate a small sample of data and then train a prediction model using this sample to annotate the full data for the relevant categories. We use a case study of a Facebook comment corpora on student loan discussion which was annotated for gender, military affiliation, age-group, political leaning, race, stance, topicalilty, neoliberlistic views and civility of the comment. We release three datasets of Facebook comments for further research at: https://github.com/socialmediaie/StudentDebtFbComments

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