Understanding Blogs through the Lens of Readers’ Comments

Authors

  • Abhilasha Sancheti Big data Experience Lab, Adobe Research, Bangalore
  • Natwar Modani Big data Experience Lab, Adobe Research, Bangalore
  • Gautam Choudhary Department of Computer Science, Indian Institute of Technology, Roorkee
  • Chintha Priyadarshini Department of Mathematics, Indian Institute of Technology, Kanpur
  • Sai Sandeep Mparthi Moparthi Department of Computer Science, Indian Institute of Technology, Bombay

DOI:

https://doi.org/10.13053/cys-23-3-3237

Keywords:

Classification, comments association, support vector machine, feature selection

Abstract

In order to keep their audience engaged, authors need to make sure that the blogs or articles they write cater to the taste of their audience and are understood by them. With the rapid proliferation of online blogging websites, the participation of readers by expressing their opinions and reviews has also increased in the form of comments on the blogs. These comments are valuable source for the authors to understand how their audience are perceiving their blogs. We believe that associating comments to the specific part of the blog they refer to will help authorin getting insights about parts of the blog which are being discussed and the questions or concerns that readers have about those parts. Moreover, categorizing these comments will further aid the author in imbibing the comments. In this work, we describe a method to associate comments to the specific parts of the blog and introduce a hierarchical way to categorize the comments as Suggestion, Agreement, Disagreement or Question.

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Published

2019-09-25

Issue

Vol. 23 No. 3 (2019): Thematic issue: Computational Linguistics (Guest Editor A. Gelbukh)

Section

Articles of the Thematic Issue

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