TY - GEN
T1 - AttitudeBuzz
T2 - IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015
AU - Cohn, Jason
AU - Kuntz, Alex
AU - Birnbaum, Lawrence A
N1 - Funding Information:
ACKNOWLEDGMENTS The authors would like to thank Miriam Boon for important discussions about geography and linguistic reclamation. We also acknowledge the efforts of nohomophobes.com [?] as one inspiration for our research. This work was supported in part by the John S. and James L. Knight Foundation, the National Science Foundation (under grant IIS-0917261), and Google.
PY - 2015/8/25
Y1 - 2015/8/25
N2 - 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.
AB - 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.
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U2 - 10.1145/2808797.2809336
DO - 10.1145/2808797.2809336
M3 - Conference contribution
AN - SCOPUS:84962523352
T3 - Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015
SP - 1569
EP - 1570
BT - Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015
A2 - Pei, Jian
A2 - Tang, Jie
A2 - Silvestri, Fabrizio
PB - Association for Computing Machinery, Inc
Y2 - 25 August 2015 through 28 August 2015
ER -