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首页> 外文会议>International Workshop on Mining and Analyzing Social Networks for Decision Support;International Workshop on Social Network Analysis in Applications;International Workshop on Dynamics in Networks;Social Media and Risk;International Symposium on Network Enabled Health Informatics, Biomedicine and Bioinformatics;International Symposium on Foundations of Open Source Intelligence and Security Informatics;International Symposium on Foundations and Applications of Big Data Analytics;Multiplex Attributed Networks Mining;IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining >AttitudeBuzz: Using social media data to localize complex attitudes
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AttitudeBuzz: Using social media data to localize complex attitudes

机译：AttitudeBuzz：使用社交媒体数据定位复杂的态度

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摘要

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.
机译：AttitudeBuzz是一个基于地理位置的社交媒体数据分析并呈现复杂社交态度的系统。该系统通过学习围绕查询域中心的可配置词典中的调制器，使用机器学习模型对此类数据（尤其是Twitter）应用特定于领域的高度情感分析。培训数据是从已知特定态度或意见占主导地位的地理区域获取的。我们将AttitudeBuzz应用于Twitter上表达的恐同态度领域。呈现最终的用户界面，并描述和分析机器学习模型。

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