Dissertation/Thesis Abstract

Assessing situations on social media: Temporal, demographic, and personality influences on situation experience
by Serfass, David G., Ph.D., Florida Atlantic University, 2016, 114; 10172674
Abstract (Summary)

Social media posts are used to examine what people experience in their everyday lives. A new method is developed for assessing the situational characteristics of social media posts based on the words used in these posts. To accomplish this, machine learning models are built that accurately approximate the judgments of human raters. This new method of situational assessment is applied on two of the most popular social media sites: Twitter and Facebook. Millions of Tweets and Facebook statuses are analyzed. Temporal patterns of situational experiences are found. Geographic and gender differences in experience are examined. Relationships between personality and situation experience were also assessed. Implications of these finding and future applications of this new method of situational assessment are discussed.

Indexing (document details)
Advisor: Sherman, Ryne A., Nowak, Andrzej
School: Florida Atlantic University
School Location: United States -- Florida
Source: DAI-B 78/02(E), Dissertation Abstracts International
Subjects: Social psychology, Personality psychology, Quantitative psychology, Web Studies
Keywords: Machine learning, Personality, Situations, Social media, Text analysis, Twitter
Publication Number: 10172674
ISBN: 978-1-369-27426-4
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