Exploiting New Sentiment-Based Meta-level Features for Effective Sentiment Analysis
暂无分享,去创建一个
[1] Mike Thelwall,et al. The Heart and Soul of the Web? Sentiment Strength Detection in the Social Web with SentiStrength , 2017 .
[2] T. Kalamboukis,et al. Combining Clustering with Classification for Spam Detection in Social Bookmarking Systems ? , 2008 .
[3] Junlan Feng,et al. Robust Sentiment Detection on Twitter from Biased and Noisy Data , 2010, COLING.
[4] Ming Wu,et al. Sentiment Classification Analysis of Chinese Microblog Network , 2015, CompleNet.
[5] Theodore Kalamboukis,et al. Using clustering to enhance text classification , 2007, SIGIR.
[6] Raj Jain,et al. The art of computer systems performance analysis - techniques for experimental design, measurement, simulation, and modeling , 1991, Wiley professional computing.
[7] Chih-Jen Lin,et al. LIBLINEAR: A Library for Large Linear Classification , 2008, J. Mach. Learn. Res..
[8] Fabrício Benevenuto,et al. Comparing and combining sentiment analysis methods , 2013, COSN '13.
[9] Katja Markert,et al. From Words to Senses: A Case Study of Subjectivity Recognition , 2008, COLING.
[10] Andrea Esuli,et al. SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining , 2010, LREC.
[11] Ronen Feldman,et al. Techniques and applications for sentiment analysis , 2013, CACM.
[12] Adam Kowalczyk,et al. Using Unlabelled Data for Text Classification through Addition of Cluster Parameters , 2002, International Conference on Machine Learning.
[13] Fabrício Benevenuto,et al. iFeel: a system that compares and combines sentiment analysis methods , 2014, WWW.
[14] Arvid Kappas,et al. Sentiment in short strength detection informal text , 2010, J. Assoc. Inf. Sci. Technol..
[15] David A. Shamma,et al. Characterizing debate performance via aggregated twitter sentiment , 2010, CHI.
[16] Ian H. Witten,et al. Issues in Stacked Generalization , 2011, J. Artif. Intell. Res..
[17] Thierson Couto,et al. On Efficient Meta-Level Features for Effective Text Classification , 2014, CIKM.
[18] Rada Mihalcea,et al. Multilingual Subjectivity Analysis Using Machine Translation , 2008, EMNLP.
[19] Ellen Riloff,et al. Creating Subjective and Objective Sentence Classifiers from Unannotated Texts , 2005, CICLing.
[20] Thierson Couto,et al. An Efficient and Scalable MetaFeature-based Document Classification Approach based on Massively Parallel Computing , 2015, SIGIR.
[21] Yiming Yang,et al. Multilabel classification with meta-level features , 2010, SIGIR.
[22] Bo Pang,et al. A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts , 2004, ACL.
[23] Andrei Popescu-Belis,et al. Sentiment analysis of user comments for one-class collaborative filtering over ted talks , 2013, SIGIR.
[24] Cornelia Caragea,et al. Using non-lexical features for identifying factual and opinionative threads in online forums , 2014, Knowl. Based Syst..
[25] S. Albayrak,et al. Language-Independent Twitter Sentiment Analysis , 2012 .
[26] Fabrício Benevenuto,et al. A Benchmark Comparison of State-of-the-Practice Sentiment Analysis Methods , 2015, ArXiv.
[27] Bernard Zenko,et al. Is Combining Classifiers with Stacking Better than Selecting the Best One? , 2004, Machine Learning.
[28] Eric Gilbert,et al. VADER: A Parsimonious Rule-Based Model for Sentiment Analysis of Social Media Text , 2014, ICWSM.
[29] Yiming Yang,et al. Multilabel classification with meta-level features in a learning-to-rank framework , 2011, Machine Learning.
[30] Christopher D. Manning,et al. Introduction to Information Retrieval , 2010, J. Assoc. Inf. Sci. Technol..
[31] Daniel Dajun Zeng,et al. Twitter Sentiment Analysis: A Bootstrap Ensemble Framework , 2013, 2013 International Conference on Social Computing.
[32] Estevam R. Hruschka,et al. Tweet sentiment analysis with classifier ensembles , 2014, Decis. Support Syst..
[33] Fabrício Benevenuto,et al. On the combination of "off-the-shelf" sentiment analysis methods , 2016, SAC.