Sentiment Analysis: What's Your Opinion?

For more than 10 years now, Sentiment Analysis has enjoyed enormous popularity in Computational Linguistics, one main reason being its great potential for practical applications, predominantly (but not only) for industrial purposes. We observe a tendency that early work referred to certain theoretical notions of Subjectivity, whereas a lot of the later approaches follow the ‘engineering’ perspective that can include using terminology somewhat indiscriminately and are not aiming at making progress with the underlying theoretical issues. In this paper, we first survey some important notions surrounding “Subjectivity” in Linguistics and Psychology, trying to broaden the perspective of standard opinion analysis. Thereafter, we take a snapshot of the state of the art in computational Sentiment Analysis, as it has developed since roughly 2000. Combining these two viewpoints leads us to assessing the gap between the broader notion of Subjectivity Analysis and the subfields that language technology research tends to focus on. We suggest a few potential research directions that could help narrowing this gap.

[1]  Bing Liu,et al.  Mining Opinion Features in Customer Reviews , 2004, AAAI.

[2]  Andrew Ortony,et al.  The Cognitive Structure of Emotions , 1988 .

[3]  A. Verhagen Constructions of Intersubjectivity: Discourse, Syntax, and Cognition , 2007 .

[4]  Michael Wiegand,et al.  Hybrid approaches for sentiment analysis , 2011 .

[5]  Bo Pang,et al.  A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts , 2004, ACL.

[6]  Philipp Cimiano,et al.  Bi-directional Inter-dependencies of Subjective Expressions and Targets and their Value for a Joint Model , 2013, ACL.

[7]  Andrea Esuli,et al.  Determining the semantic orientation of terms through gloss classification , 2005, CIKM '05.

[8]  Iryna Gurevych,et al.  Sentence and Expression Level Annotation of Opinions in User-Generated Discourse , 2010, ACL.

[9]  Marshall S. Smith,et al.  The general inquirer: A computer approach to content analysis. , 1967 .

[10]  Ulli Waltinger,et al.  GermanPolarityClues: A Lexical Resource for German Sentiment Analysis , 2010, LREC.

[11]  Maite Taboada,et al.  Lexicon-Based Methods for Sentiment Analysis , 2011, CL.

[12]  南出 康世,et al.  Macmillan English dictionary : for advanced learners , 2007 .

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

[14]  Claire Cardie,et al.  Annotating Expressions of Opinions and Emotions in Language , 2005, Lang. Resour. Evaluation.

[15]  Christine Thielen,et al.  Ein kleines und erweitertes Tagset fürs Deutsche , 1996 .

[16]  Navneet Kaur,et al.  Opinion mining and sentiment analysis , 2016, 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom).

[17]  R. Langacker Foundations of Cognitive Grammar: Volume I: Theoretical Prerequisites , 1987 .

[18]  Siddarth Ramaswamy Visualization of the Sentiment of the Tweets. , 2011 .

[19]  Philipp Cimiano,et al.  The USAGE review corpus for fine grained multi lingual opinion analysis , 2014, LREC.

[20]  James Pustejovsky,et al.  Annotating, Extracting and Reasoning About Time and Events , 2005, Annotating, Extracting and Reasoning about Time and Events.

[21]  Mitsuru Ishizuka,et al.  Emotion Sensitive News Agent (ESNA): A system for user centric emotion sensing from the news , 2010, Web Intell. Agent Syst..

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

[23]  A. Dobrescu Methods and resources for sentiment analysis in multilingual documents of different text types , 2011 .

[24]  Jeannett Martin,et al.  The Language of Evaluation: Appraisal in English , 2005 .

[25]  Gerhard Heyer,et al.  SentiWS - A Publicly Available German-language Resource for Sentiment Analysis , 2010, LREC.

[26]  Michael Rundell,et al.  Macmillan English Dictionary for Advanced Learners , 2002 .

[27]  Richard Hudson,et al.  Foundations of cognitive grammar. Volume 1. Theoretical prerequisites , 1990 .

[28]  K. Bühler Sprachtheorie: Die Darstellungsfunktion der Sprache , 1934 .

[29]  R. Langacker Foundations of cognitive grammar , 1983 .

[30]  J. Anscombre,et al.  L'argumentation dans la langue , 1976 .

[31]  Maite Taboada,et al.  Analyzing Appraisal Automatically , 2004 .

[32]  P. Dendale,et al.  Introduction: evidentiality and related notions , 2001 .

[33]  Simon Clematide,et al.  MLSA - A Multi-layered Reference Corpus for German Sentiment Analysis , 2012, LREC.

[34]  Janyce Wiebe,et al.  Tracking Point of View in Narrative , 1994, Comput. Linguistics.

[35]  Bo Pang,et al.  Thumbs up? Sentiment Classification using Machine Learning Techniques , 2002, EMNLP.

[36]  Janyce Wiebe,et al.  Articles: Recognizing Contextual Polarity: An Exploration of Features for Phrase-Level Sentiment Analysis , 2009, CL.

[37]  Junlan Feng,et al.  Robust Sentiment Detection on Twitter from Biased and Noisy Data , 2010, COLING.

[38]  Silvia Bernardini,et al.  The WaCky wide web: a collection of very large linguistically processed web-crawled corpora , 2009, Lang. Resour. Evaluation.

[39]  Christopher Potts,et al.  Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank , 2013, EMNLP.

[40]  Peter D. Turney Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews , 2002, ACL.

[41]  J. Carbonell Subjective understanding, computer models of belief systems , 1981 .

[42]  B. Alexandra,et al.  Rethinking Sentiment Analysis in the News: from Theory to Practice and back , 2009 .

[43]  郑有志 谈谈A Grammar of Contemporary English对于分句与句子问题的若干处理 , 1993 .

[44]  Theresa Wilson,et al.  Annotating Subjective Content in Meetings , 2008, LREC.

[45]  Maite Taboada,et al.  Genre-Based Paragraph Classification for Sentiment Analysis , 2009, SIGDIAL Conference.

[46]  F. Heider The psychology of interpersonal relations , 1958 .

[47]  Bo Pang,et al.  Seeing Stars: Exploiting Class Relationships for Sentiment Categorization with Respect to Rating Scales , 2005, ACL.

[48]  Saif Mohammad,et al.  NRC-Canada-2014: Detecting Aspects and Sentiment in Customer Reviews , 2014, *SEMEVAL.

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