Making large-scale support vector machine learning practical
Advances in kernel methods
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Learning Subjective Adjectives from Corpora
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Sentiment analysis: capturing favorability using natural language processing
Proceedings of the 2nd international conference on Knowledge capture
A machine learning approach to coreference resolution of noun phrases
Computational Linguistics - Special issue on computational anaphora resolution
Predicting the semantic orientation of adjectives
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Graph-based text classification: learn from your neighbors
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Recognizing contextual polarity in phrase-level sentiment analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Identifying sources of opinions with conditional random fields and extraction patterns
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Non-projective dependency parsing using spanning tree algorithms
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
The utility of linguistic rules in opinion mining
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Extracting opinions, opinion holders, and topics expressed in online news media text
SST '06 Proceedings of the Workshop on Sentiment and Subjectivity in Text
Robust sentiment detection on Twitter from biased and noisy data
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Enhanced sentiment learning using Twitter hashtags and smileys
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
User-level sentiment analysis incorporating social networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Topic sentiment analysis in twitter: a graph-based hashtag sentiment classification approach
Proceedings of the 20th ACM international conference on Information and knowledge management
Extracting semantic annotations from twitter
Proceedings of the fourth workshop on Exploiting semantic annotations in information retrieval
Mining the interests of Chinese microbloggers via keyword extraction
Frontiers of Computer Science in China
Textual and contextual patterns for sentiment analysis over microblogs
Proceedings of the 21st international conference companion on World Wide Web
Emotion tokens: bridging the gap among multilingual twitter sentiment analysis
AIRS'11 Proceedings of the 7th Asia conference on Information Retrieval Technology
Content vs. context for sentiment analysis: a comparative analysis over microblogs
Proceedings of the 23rd ACM conference on Hypertext and social media
Entity-centric topic-oriented opinion summarization in twitter
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Context-Sensitive sentiment classification of short colloquial text
IFIP'12 Proceedings of the 11th international IFIP TC 6 conference on Networking - Volume Part I
Improving tweet stream classification by detecting changes in word probability
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Identifying entity aspects in microblog posts
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
User-sentiment topic model: refining user's topics with sentiment information
Proceedings of the ACM SIGKDD Workshop on Mining Data Semantics
Learning for microblogs with distant supervision: political forecasting with Twitter
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
QuickView: NLP-based tweet search
ACL '12 Proceedings of the ACL 2012 System Demonstrations
Automatically constructing a normalisation dictionary for microblogs
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Recognizing arguing subjectivity and argument tags
ExProM '12 Proceedings of the Workshop on Extra-Propositional Aspects of Meaning in Computational Linguistics
If you are happy and you know it... tweet
Proceedings of the 21st ACM international conference on Information and knowledge management
Lexical normalization for social media text
ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on twitter and microblogging services, social recommender systems, and CAMRa2010: Movie recommendation in context
Identifying same wavelength groups from twitter: a sentiment based approach
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part II
Sentiment and topic analysis on social media: a multi-task multi-label classification approach
Proceedings of the 5th Annual ACM Web Science Conference
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
I act, therefore I judge: network sentiment dynamics based on user activity change
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Identifying purpose behind electoral tweets
Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining
Combining strengths, emotions and polarities for boosting Twitter sentiment analysis
Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining
Evaluation of an algorithm for aspect-based opinion mining using a lexicon-based approach
Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining
Keyword-Based Sentiment Mining using Twitter
International Journal of Ambient Computing and Intelligence
Expert Systems with Applications: An International Journal
Ranked WordNet graph for Sentiment Polarity Classification in Twitter
Computer Speech and Language
Opinion Bias Detection with Social Preference Learning in Social Data
International Journal on Semantic Web & Information Systems
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Sentiment analysis on Twitter data has attracted much attention recently. In this paper, we focus on target-dependent Twitter sentiment classification; namely, given a query, we classify the sentiments of the tweets as positive, negative or neutral according to whether they contain positive, negative or neutral sentiments about that query. Here the query serves as the target of the sentiments. The state-of-the-art approaches for solving this problem always adopt the target-independent strategy, which may assign irrelevant sentiments to the given target. Moreover, the state-of-the-art approaches only take the tweet to be classified into consideration when classifying the sentiment; they ignore its context (i.e., related tweets). However, because tweets are usually short and more ambiguous, sometimes it is not enough to consider only the current tweet for sentiment classification. In this paper, we propose to improve target-dependent Twitter sentiment classification by 1) incorporating target-dependent features; and 2) taking related tweets into consideration. According to the experimental results, our approach greatly improves the performance of target-dependent sentiment classification.