Ranking of Products through Blog Analysis

  • Niladri Chatterjee
  • Sumit Bisai
  • Prasenjit Chakraborty


Many web blogs contain comments of users on different products. Such comments are often helpful for a naive user to decide which particular product (from among various alternatives available in the market) he/she is interested in. However, manual analysis of these blogs is timeconsuming. In this work we propose a tool for automatic analysis of blogs on different products, and rank them on the basis of certain key features. The task however is not straightforward as users’ comments are often replete with ungrammatical or poorly-structured sentences, incoherence of themes, usages of synonyms, and many other usual NLP problems, which need to be dealt with appropriately. The overall procedure takes the following steps: Preprocessing, POS tagging, Brand identification, Feature identification and Ranking. The scheme has been tested on blogs of Laptops and Automobiles. The initial results are found to be very promising.


Sentiment Analysis Sentiment Classification Movie Review User Review Local Count 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 3.
    James A.: Natural Language Understanding, Pearson, New Delhi (1995)Google Scholar
  2. 6.
    Zhuang L., Jing F., Zhu X.: Movie review mining and summarization. In Proceedings of the 15th ACM international conference on Information and knowledge management (CIKM), pp. 43–50 (2006)Google Scholar
  3. 7.
    Pang B., Lee L., Vaithyanathan S.: Thumbs up? Sentiment classification using machine learning techniques. In Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2002)Google Scholar
  4. 8.
    Melville P., Gryc W., Lawrence R.: Incorporating Background Knowledge into Text Categorization for Improved Sentiment Analysis. Technical Report, IBM (2008)Google Scholar

Copyright information

© Indian Institute of Information Technology, India 2009

Authors and Affiliations

  • Niladri Chatterjee
    • 1
  • Sumit Bisai
    • 1
  • Prasenjit Chakraborty
    • 2
  1. 1.Department of Mathematics. IITNew Delhi
  2. 2.IBM India Pvt LtdBangalore

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