Opinion mining in legal blogs

We perform a survey into the scope and utility of opinion mining in legal Weblogs (a.k.a. blawgs). The number of 'blogs' in the legal domain is growing at a rapid pace and many potential applications for opinion detection and monitoring are arising as a result. We summarize current approaches to opinion mining before describing different categories of blawgs and their potential impact on the law and the legal profession. In addition to educating the community on recent developments in the legal blog space, we also conduct some introductory opinion mining trials. We first construct a Weblog test collection containing blog entries that discuss legal search tools. We subsequently examine the performance of a language modeling approach deployed for both subjectivity analysis (i.e., is the text subjective or objective?) and polarity analysis (i.e., is the text affirmative or negative towards its subject?). This work may thus help establish early baselines for these core opinion mining tasks.

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

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

[3]  Bing Liu,et al.  Mining and summarizing customer reviews , 2004, KDD.

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

[5]  Claire Cardie,et al.  Recognizing and Organizing Opinions Expressed in the World Press , 2003, New Directions in Question Answering.

[6]  Janyce Wiebe,et al.  Learning Subjective Adjectives from Corpora , 2000, AAAI/IAAI.

[7]  Janyce Wiebe,et al.  Effects of Adjective Orientation and Gradability on Sentence Subjectivity , 2000, COLING.

[8]  Michael L. Littman,et al.  Measuring praise and criticism: Inference of semantic orientation from association , 2003, TOIS.

[9]  Takashi Inui,et al.  Extracting Semantic Orientations of Words using Spin Model , 2005, ACL.

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

[11]  Andrea Esuli,et al.  Determining Term Subjectivity and Term Orientation for Opinion Mining , 2006, EACL.

[12]  Stefano Vegnaduzzo.  Acquisition of Subjective Adjectives with Limited Resources , 2004 .

[13]  Eric K. Ringger,et al.  Pulse: Mining Customer Opinions from Free Text , 2005, IDA.

[14]  Ellen Riloff,et al.  Creating Subjective and Objective Sentence Classifiers from Unannotated Texts , 2005, CICLing.

[15]  Andrea Esuli,et al.  SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining , 2006, LREC.

[16]  Soo-Min Kim,et al.  Determining the Sentiment of Opinions , 2004, COLING.

[17]  Takamura Hiroya,et al.  Extracting Emotional Polarity of Words using Spin Model , 2004 .

[18]  W. Bruce Croft,et al.  A language modeling approach to information retrieval , 1998, SIGIR '98.

[19]  David M. Pennock,et al.  Mining the peanut gallery: opinion extraction and semantic classification of product reviews , 2003, WWW '03.

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

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

[22]  W. Bruce Croft,et al.  Computing Attitude and Affect in Text : , 2006 .

[23]  Shlomo Argamon,et al.  Using appraisal groups for sentiment analysis , 2005, CIKM '05.

[24]  Satoshi Morinaga,et al.  Mining product reputations on the Web , 2002, KDD.

[25]  Marie-Francine Moens.  Combining structured and unstructured information in a retrieval model for accessing legislation , 2005, ICAIL '05.

[26]  Ellen Riloff,et al.  Learning Extraction Patterns for Subjective Expressions , 2003, EMNLP.

[27]  J. Kamps,et al.  Words with attitude , 2002 .

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

[29]  Marco Baroni,et al.  Identifying subjective adjectives through web-based mutual information , 2004 .

[30]  Peter D. Turney.  Thumbs Up, Thumbs Down , 2013, Journal of Cell Science.

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

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