SciELO - Scientific Electronic Library Online

 
vol.17 issue2Extracting Phrases Describing Problems with Products and Services from Twitter MessagesUsing Stylistic Features for Social Power Modeling author indexsubject indexsearch form
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • Have no similar articlesSimilars in SciELO

Share


Computación y Sistemas

On-line version ISSN 2007-9737Print version ISSN 1405-5546

Abstract

BALALI, Ali; FAILI, Hesham; ASADPOUR, Masoud  and  DEHGHANI, Mostafa. A Supervised Approach for Reconstructing Thread Structure in Comments on Blogs and Online News Agencies. Comp. y Sist. [online]. 2013, vol.17, n.2, pp.207-217. ISSN 2007-9737.

There is a great deal of knowledge in online environments such as forums, chats and blogs. A large volume of comments with different subjects on a page has created a lot of complexity in following the actual conversation streams, since the reply structures of comments are generally not publicly accessible in online environments. It is beneficial to automatically reconstruct thread structure of comments to deal with such a problem. This work focuses on reconstructing thread structures on blogs and online news agencies' comment space. First, we define a set of textual and non-textual features. Then we use a learning algorithm to combine extracted features. The proposed method has been evaluated on three different datasets, which include two datasets in Persian and one in English. The accuracy ratio of the proposed model is compared with three baseline algorithms. The results reveal higher accuracy ratio for the proposed method in comparison with the baseline methods for all datasets.

Keywords : Reconstructing thread structure; reply structure; information extraction; blogs and online news agencies; machine learning; information management.

        · abstract in Spanish     · text in English     · English ( pdf )

 

Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License