Research Article

Identification and Analysis of Spam Words from Facebook Spam Comments

by  Namrata P. Bhatt, Jatinderkumar R. Saini
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 145 - Issue 2
Published: Jul 2016
Authors: Namrata P. Bhatt, Jatinderkumar R. Saini
10.5120/ijca2016910587
PDF

Namrata P. Bhatt, Jatinderkumar R. Saini . Identification and Analysis of Spam Words from Facebook Spam Comments. International Journal of Computer Applications. 145, 2 (Jul 2016), 36-38. DOI=10.5120/ijca2016910587 

                        @article{ 10.5120/ijca2016910587,
                        author  = { Namrata P. Bhatt,Jatinderkumar R. Saini },
                        title   = { Identification and Analysis of Spam Words from Facebook Spam Comments },
                        journal = { International Journal of Computer Applications },
                        year    = { 2016 },
                        volume  = { 145 },
                        number  = { 2 },
                        pages   = { 36-38 },
                        doi     = { 10.5120/ijca2016910587 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2016
                        %A Namrata P. Bhatt
                        %A Jatinderkumar R. Saini
                        %T Identification and Analysis of Spam Words from Facebook Spam Comments%T 
                        %J International Journal of Computer Applications
                        %V 145
                        %N 2
                        %P 36-38
                        %R 10.5120/ijca2016910587
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

Various posts on social media contain number of spam comments which are counterproductive. Such comments may include advertisements, abusing words or pointless arguments. Current paper presents the findings on such comments and provides the frequency of unique words after stop words filtration. Total 10 Facebook links were evaluated for spam words identification. These 10 links contained a total 13,100 comments among which 2,404 spam comments were detected. Total Spam words from Spam comments were 18,505 including Stop words and Duplicates while total unique spam words were 12,266. It has been found that the words ‘recharge’, ‘best’, ‘like’, ‘free’ and ‘god’ are the most probable spam words in the spam comments in profiles of celebrities on Facebook.

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Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Bag of Words (BOW) Facebook Spam Tokenization Vector Space Document Model (VSDM)

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