Democrats, Republicans and Starbucks Afficionados: User Classification in Twitter
M. Pennacchiotti, and A. Popescu. Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, page 430--438. New York, NY, USA, ACM, (2011)
DOI: 10.1145/2020408.2020477
Abstract
More and more technologies are taking advantage of the explosion of social media (Web search, content recommendation services, marketing, ad targeting, etc.). This paper focuses on the problem of automatically constructing user profiles, which can significantly benefit such technologies. We describe a general and robust machine learning framework for large-scale classification of social media users according to dimensions of interest. We report encouraging experimental results on 3 tasks with different characteristics: political affiliation detection, ethnicity identification and detecting affinity for a particular business.
%0 Conference Paper
%1 Pennacchiotti:2011:DRS:2020408.2020477
%A Pennacchiotti, Marco
%A Popescu, Ana-Maria
%B Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
%C New York, NY, USA
%D 2011
%I ACM
%K classification twitter webscience webscience_lecture
%P 430--438
%R 10.1145/2020408.2020477
%T Democrats, Republicans and Starbucks Afficionados: User Classification in Twitter
%U http://doi.acm.org/10.1145/2020408.2020477
%X More and more technologies are taking advantage of the explosion of social media (Web search, content recommendation services, marketing, ad targeting, etc.). This paper focuses on the problem of automatically constructing user profiles, which can significantly benefit such technologies. We describe a general and robust machine learning framework for large-scale classification of social media users according to dimensions of interest. We report encouraging experimental results on 3 tasks with different characteristics: political affiliation detection, ethnicity identification and detecting affinity for a particular business.
%@ 978-1-4503-0813-7
@inproceedings{Pennacchiotti:2011:DRS:2020408.2020477,
abstract = {More and more technologies are taking advantage of the explosion of social media (Web search, content recommendation services, marketing, ad targeting, etc.). This paper focuses on the problem of automatically constructing user profiles, which can significantly benefit such technologies. We describe a general and robust machine learning framework for large-scale classification of social media users according to dimensions of interest. We report encouraging experimental results on 3 tasks with different characteristics: political affiliation detection, ethnicity identification and detecting affinity for a particular business.},
acmid = {2020477},
added-at = {2014-04-22T08:52:17.000+0200},
address = {New York, NY, USA},
author = {Pennacchiotti, Marco and Popescu, Ana-Maria},
biburl = {https://www.bibsonomy.org/bibtex/2fc1b63825c7eb8faca87e0a41b28b14b/asmelash},
booktitle = {Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
description = {Democrats, republicans and starbucks afficionados},
doi = {10.1145/2020408.2020477},
interhash = {a1990af4b1129f17e4a697fb5cc0d93f},
intrahash = {fc1b63825c7eb8faca87e0a41b28b14b},
isbn = {978-1-4503-0813-7},
keywords = {classification twitter webscience webscience_lecture},
location = {San Diego, California, USA},
numpages = {9},
pages = {430--438},
publisher = {ACM},
series = {KDD '11},
timestamp = {2014-04-29T16:48:07.000+0200},
title = {Democrats, Republicans and Starbucks Afficionados: User Classification in Twitter},
url = {http://doi.acm.org/10.1145/2020408.2020477},
year = 2011
}