This corpus and software was used for the experiments presented in the paper:
Ivan Omar Cruz-Garcia, Alexander Gelbukh, Grigori Sidorov. Implicit Aspect Indicator Extraction for Aspect based Opinion Mining. International Journal of Computational Linguistics and Applications, Vol. 5 No. 2, 2014, pp. 135–152.
Any work that uses the dataset or software should cite the abovementioned paper(s).
License: free for non-commercial academic purposes. Any publication that benefited from these data or software must state the origin of the data and software and cite the abovementioned paper(s). We will be grateful to you if you let us know of the use of the data or software and of citing our papers. Any derived work should specify the original source and its authors and contain this license, including the publication references mentioned above. If you modify this corpus or software, correct errors in it, or add annotation/functionality to it, we will be grateful if you send us the new version, to be available from this site. See also individual license files below.
This corpus is based on the Customer Review Datasets (5 products) corpus described in: M. Hu, B. Liu, Mining and summarizing customer reviews, in: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2004, pp. 168–177; see Bing Liu's Opinion Lexicon page. We used the text of that corpus, removed all original annotations and comments, and manually added annotation of implicit aspects and implicit aspect indicators.
This resource is useful for sentiment analysis, opinion mining, sentiment polarity detection, social network analysis, emotion analysis, etc.
Download the corpus for implicit aspect extraction and implicit aspect indicator extraction, license, and Readme in one ZIP archive.
Download individual files:
None so far.
Implicit aspects indicators are similar to the implicit aspect expressions, with differences discussed in the abovementioned paper. The software was used to train a Conditional Random Fields (CRF) classifier with the corpus above for extracting implicit aspect indicators.
This tool is useful for sentiment analysis, opinion mining, sentiment polarity detection, social network analysis, emotion analysis, etc.
Download the implicit aspects indicators extraction tool, license, and Readme in one ZIP archive.
None so far.