2013/08/08 by Pollyanna Gonçalves, Gonçalves, Pollyanna, Fabrício Benevenuto +3
Computer Science · Social Sciences · Psychology · #Sentiment Analysis and Opinion Mining #Misinformation and Its Impacts #Mental Health via Writing
paper · pdf · doi:10.48550/arxiv.1308.1857
Online social networks have become a major communication platform, where people share their thoughts and opinions about any topic real-time. The short text updates people post in these network contain emotions and moods, which when measured collectively can unveil the public mood at population level and have exciting implications for businesses, governments, and societies. Therefore, there is an urgent need for developing solid methods for accurately measuring moods from large-scale social media data. In this paper, we propose PANAS-t, which measures sentiments from short text updates in Twitter based on a well-established psychometric scale, PANAS (Positive and Negative Affect Schedule). We test the efficacy of PANAS-t over 10 real notable events drawn from 1.8 billion tweets and demonstrate that it can efficiently capture the expected sentiments of a wide variety of issues spanning tragedies, technology releases, political debates, and healthcare.