Hope and fear: Interpreting perspectives by integrating sentiment and event factuality

Both sentiment and event factuality are fundamental information levels for our understanding of events mentioned in news texts. Most research so far has focused on either modeling opinions or factuality. In this paper, we propose a model that combines the two for the extraction and interpretation of perspectives on events. By doing so, we can explain the way people perceive changes in (their belief of) the world as a function of their fears of changes to the bad or their hopes of changes to the good. This study seeks to examine the effectiveness of this approach by applying factuality annotations, based on FactBank, on top of the MPQA Corpus, a corpus containing news texts annotated for sentiments and other private states. Our findings suggest that this approach can be valuable for the understanding of perspectives, but that there is still some work to do on the refinement of the integration.

[1]  Noriko Kando,et al.  Certainty Identification in Texts: Categorization Model and Manual Tagging Results , 2023 .

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

[3]  János Csirik,et al.  The BioScope corpus: biomedical texts annotated for uncertainty, negation and their scopes , 2008, BMC Bioinformatics.

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

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

[6]  Rashmi Prasad,et al.  The Penn Discourse Treebank , 2004, LREC.

[7]  Daniel Gildea,et al.  The Proposition Bank: An Annotated Corpus of Semantic Roles , 2005, CL.

[8]  Theresa Wilson.  Fine-grained subjectivity and sentiment analysis: recognizing the intensity, polarity, and attitudes of private states , 2008 .

[9]  Victoria L. Rubin.  Stating with Certainty or Stating with Doubt: Intercoder Reliability Results for Manual Annotation of Epistemically Modalized Statements , 2007, NAACL.

[10]  Claire Cardie,et al.  Identifying Sources of Opinions with Conditional Random Fields and Extraction Patterns , 2005, HLT.

[11]  Eduard Hovy,et al.  Identifying Opinion Holders for Question Answering in Opinion Texts , 2005 .

[12]  Valentina Bartalesi Lenzi,et al.  CAT: the CELCT Annotation Tool , 2012, LREC.

[13]  Dan Jurafsky,et al.  Automatic Extraction of Opinion Propositions and their Holders , 2004 .

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

[15]  James Pustejovsky,et al.  FactBank: a corpus annotated with event factuality , 2009, Lang. Resour. Evaluation.