Subsentential Sentiment on a Shoestring: A Crosslingual Analysis of Compositional Classification

Sentiment analysis has undergone a shift from document-level analysis, where labels expresses the sentiment of a whole document or whole sentence, to subsentential approaches, which assess the contribution of individual phrases, in particular including the composition of sentiment terms and phrases such as negators and intensifiers. Starting from a small sentiment treebank modeled after the Stanford Sentiment Treebank of Socher et al. (2013), we investigate suitable methods to perform compositional sentiment classification for German in a data-scarce setting, harnessing cross-lingual methods as well as existing general-domain lexical resources.

[1]  Christopher D. Manning,et al.  Parsing Three German Treebanks: Lexicalized and Unlexicalized Baselines , 2008 .

[2]  Angela Fahrni,et al.  Old Wine or Warm Beer : Target-Specific Sentiment Analysis of Adjectives , .

[3]  Ming Zhou,et al.  Adaptive Multi-Compositionality for Recursive Neural Models with Applications to Sentiment Analysis , 2014, AAAI.

[4]  Andrew Y. Ng,et al.  Semantic Compositionality through Recursive Matrix-Vector Spaces , 2012, EMNLP.

[5]  Thierry Declerck,et al.  SentiMerge: Combining Sentiment Lexicons in a Bayesian Framework , 2014, LG-LP@COLING.

[6]  Anna Corazza The Berkeley Parser at the EVALITA 2009 Constituency Parsing Task , 2009 .

[7]  Jörg Tiedemann Lingua-Align: An Experimental Toolbox for Automatic Tree-to-Tree Alignment , 2010, LREC.

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

[9]  Kentaro Inui,et al.  Dependency Tree-based Sentiment Classification using CRFs with Hidden Variables , 2010, NAACL.

[10]  Jeffrey Pennington,et al.  Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions , 2011, EMNLP.

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

[12]  Martin Volk,et al.  Automatic node insertion for treebank deepening , 2010 .

[13]  Hongyu Guo,et al.  An Empirical Study on the Effect of Negation Words on Sentiment , 2014, ACL.

[14]  Dan Klein,et al.  Learning Accurate, Compact, and Interpretable Tree Annotation , 2006, ACL.

[15]  George Karypis,et al.  Hierarchical Clustering Algorithms for Document Datasets , 2005, Data Mining and Knowledge Discovery.

[16]  Claire Cardie,et al.  Adapting a Polarity Lexicon using Integer Linear Programming for Domain-Specific Sentiment Classification , 2009, EMNLP.

[17]  FayyadUsama,et al.  Hierarchical Clustering Algorithms for Document Datasets , 2005 .

[18]  Ulli Waltinger,et al.  Sentiment Analysis Reloaded - A Comparative Study on Sentiment Polarity Identification Combining Machine Learning and Subjectivity Features , 2010, WEBIST.

[19]  Kevin Duh,et al.  Is Machine Translation Ripe for Cross-Lingual Sentiment Classification? , 2011, ACL.

[20]  Ben Taskar,et al.  Better Alignments = Better Translations? , 2008, ACL.

[21]  Gholamreza Haffari,et al.  The Haves and the Have-Nots: Leveraging Unlabelled Corpora for Sentiment Analysis , 2013, ACL.

[22]  Dan Klein,et al.  Less Grammar, More Features , 2014, ACL.

[23]  Philip J. Stone,et al.  Extracting Information. (Book Reviews: The General Inquirer. A Computer Approach to Content Analysis) , 1967 .

[24]  Christopher D. Manning,et al.  Baselines and Bigrams: Simple, Good Sentiment and Topic Classification , 2012, ACL.

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

[26]  Katja Markert,et al.  Subjectivity Recognition on Word Senses via Semi-supervised Mincuts , 2009, HLT-NAACL.

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

[28]  Claire Cardie,et al.  Compositional Matrix-Space Models for Sentiment Analysis , 2011, EMNLP.

[29]  Rada Mihalcea,et al.  Porting Multilingual Subjectivity Resources across Languages , 2013, IEEE Transactions on Affective Computing.

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

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

[32]  Marie Candito,et al.  Parsing Word Clusters , 2010, SPMRL@NAACL-HLT.

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

[34]  Xiaojun Wan,et al.  Co-Training for Cross-Lingual Sentiment Classification , 2009, ACL.

[35]  Ulli Waltinger,et al.  An Empirical Study on Machine Learning-Based Sentiment Classification Using Polarity Clues , 2010, WEBIST.

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

[37]  Manfred Klenner,et al.  PolArt: A Robust Tool for Sentiment Analysis , 2009, NODALIDA.

[38]  Claire Cardie,et al.  Learning with Compositional Semantics as Structural Inference for Subsentential Sentiment Analysis , 2008, EMNLP.

[39]  Jörg Tiedemann,et al.  Parallel Data, Tools and Interfaces in OPUS , 2012, LREC.

[40]  Xavier Carreras,et al.  Simple Semi-supervised Dependency Parsing , 2008, ACL.