AttitudeBuzz

Autor: Alex Kuntz, Jason Cohn, Lawrence Birnbaum
Rok vydání: 2015
Předmět:
Zdroj: ASONAM
DOI: 10.1145/2808797.2809336
Popis: AttitudeBuzz is a system that analyzes and presents complex social attitudes based on geolocated social media data. The system uses a machine learning model to apply highly domain-specific sentiment analysis to such data, specifically Twitter, by learning modulators around a configurable lexicon central to the domain of inquiry. Training data are acquired from geographical areas where a specific attitude or opinion is known to dominate. We apply AttitudeBuzz to the domain of homophobic attitudes expressed on Twitter. The resulting user interface is presented and the machine learning model described and analyzed.
Databáze: OpenAIRE