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AspectFrameNet: a frameNet extension for analysis of sentiments around product aspects

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Abstract

In the real-world scenarios, customer tries to evaluate a product based on sentiments conveyed by its users or reviewers. AspectFrameNet provides a framework that helps the semantic analysis of text inputs from social feeds and news (Voice of Customer) by disambiguating the contexts in which the lexical units are used. To this end, we have used this framework in analysing sentiments around different aspects of internet of things. We have tested this framework for 31 interrelated aspects in mobile domain and three possible sentiments (positive, negative and neutral).

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Notes

  1. The Stanford tools and guidelines are downloadable from: http://nlp.stanford.edu/software/.

  2. The ARK-Tweet-NLP tools of CMU are downloadable from: http://www.ark.cs.cmu.edu/TweetNLP/.

  3. CRF++: Yet Another CRF toolkit Version 0.58 has been downloaded from: http://crfpp.googlecode.com/svn/trunk/doc/index.html?source=navbar#download.

  4. LIBSVM Version 3.20 has been downloaded from: http://www.csie.ntu.edu.tw/~cjlin/libsvm/.

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Acknowledgments

The authors would like to thank Mr. Tripun Goel, Mr. Krishnamraju Murali Venkata Mutyala, Mr. Chandragouda Patil, Mr. Ramachandran Narasimhamurthy, Mr. Srinidhi Nirgunda Seshadri, Dr. Pinaki Bhaskar, Dr. Hanumantha Rao Susarla, Dr. Shankar M. Venkatesan and Dr. Nitin Dileep Salodkar for reviewing and guiding us throughout the work.

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Authors and Affiliations

  1. Samsung R&D Institute India, Bangalore, India

    Sanjay Chatterji, Nitish Varshney & Ranjan Kumar Rahul

Authors
  1. Sanjay Chatterji
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  2. Nitish Varshney
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  3. Ranjan Kumar Rahul
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Corresponding author

Correspondence to Sanjay Chatterji.

Appendix

Appendix

nsubj :

Nominal subject

dobj :

Direct object

amod :

Adjectival modifier

advmod :

Adverb modifier

pobj :

Object of a preposition

pcomp :

Prepositional complement

conj :

Conjunction

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Chatterji, S., Varshney, N. & Rahul, R.K. AspectFrameNet: a frameNet extension for analysis of sentiments around product aspects. J Supercomput 73, 961–972 (2017). https://doi.org/10.1007/s11227-016-1808-6

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