Sentiment Analysis of Name Entity for Text

Recent years, big data has attracted increasing interest. Sentiment analysis from microblog as one kind of big data also receive great attention. Some recent research works are not suitable for sentiment analysis as the result that users prefer to express their feelings in individual ways. In this paper, a framework is proposed to calculate sentiment for aspects of event. Based on some state of art technologies, we build up one flowchart to get sentiment for aspects of event. During the process, name entities with the same meaning are clustered and sentiment carrier are filtered. In this way sentiment can be got even user express feeling for the same object with different words.

[1]  Rada Mihalcea,et al.  TextRank: Bringing Order into Text , 2004, EMNLP.

[2]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[3]  Andrew Y. Ng,et al.  Improving Word Representations via Global Context and Multiple Word Prototypes , 2012, ACL.

[4]  Ali A. Ghorbani,et al.  Lexical-Syntactical Patterns for Subjectivity Analysis of Social Issues , 2013, AMT.

[5]  Zhendong Niu,et al.  Automatic construction of domain-specific sentiment lexicon based on constrained label propagation , 2014, Knowl. Based Syst..

[6]  Gerard Salton,et al.  Term-Weighting Approaches in Automatic Text Retrieval , 1988, Inf. Process. Manag..

[7]  Lan Chen,et al.  Semantic Link Network-Based Model for Organizing Multimedia Big Data , 2014, IEEE Transactions on Emerging Topics in Computing.

[8]  Yunhuai Liu,et al.  Crowdsourcing based social media data analysis of urban emergency events , 2017, Multimedia Tools and Applications.

[9]  Kam-Fai Wong,et al.  Interpreting TF-IDF term weights as making relevance decisions , 2008, TOIS.

[10]  Janyce Wiebe,et al.  Just How Mad Are You? Finding Strong and Weak Opinion Clauses , 2004, AAAI.

[11]  Jeffrey Pennington,et al.  GloVe: Global Vectors for Word Representation , 2014, EMNLP.

[12]  Xue Chen,et al.  Building Association Link Network for Semantic Link on Web Resources , 2011, IEEE Transactions on Automation Science and Engineering.

[13]  Mingliang Chen,et al.  Building emotional dictionary for sentiment analysis of online news , 2014, World Wide Web.

[14]  Claire Cardie,et al.  Identifying Expressions of Opinion in Context , 2007, IJCAI.

[15]  Lan Chen,et al.  Knowle: A semantic link network based system for organizing large scale online news events , 2015, Future Gener. Comput. Syst..

[16]  W. G. Parrott,et al.  Emotions in social psychology : essential readings , 2001 .

[17]  Lan Chen,et al.  Semantic enhanced cloud environment for surveillance data management using video structural description , 2014, Computing.

[18]  Lan Chen,et al.  Semantic based representing and organizing surveillance big data using video structural description technology , 2015, J. Syst. Softw..

[19]  Mike Y. Chen,et al.  Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web , 2001 .

[20]  이주연,et al.  Latent Dirichlet Allocation (LDA) 모델 기반의 인공지능(A.I.) 기술 관련 연구 활동 및 동향 분석 , 2018 .

[21]  Janyce Wiebe,et al.  Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis , 2005, HLT.

[22]  Kathleen R. McKeown,et al.  Predicting the semantic orientation of adjectives , 1997 .

[23]  Vasileios Hatzivassiloglou,et al.  Predicting the Semantic Orientation of Adjectives , 1997, ACL.

[24]  Lillian Lee,et al.  Opinion Mining and Sentiment Analysis , 2008, Found. Trends Inf. Retr..

[25]  Chen Guolong Identify Sentiment-Objects from Chinese Sentences Based on Cascaded Conditional Random Fields , 2013 .

[26]  Gerard Salton,et al.  A vector space model for automatic indexing , 1975, CACM.

[27]  Jing Liu,et al.  An Integrated Method for Micro-blog Subjective Sentence Identification Based on Three-Way Decisions and Naive Bayes , 2014, RSKT.