• Aug 25, 2016 News!Vol.4, No.3 has been published with online version. 15 peer reviewed articles from 3 specific areas are published in this issue.   [Click]
  • May 03, 2016 News!Vol. 3, No. 3 has been indexed by EI (Inspec).   [Click]
  • May 03, 2016 News!Vol. 3, No. 2 has been indexed by EI (Inspec).   [Click]
General Information
    • ISSN: 2301-3559
    • Frequency: Quarterly
    • DOI: 10.18178/LNSE
    • Editor-in-Chief: Prof. Jemal Antidze
    • Executive Editor: Ms. Nina Lee
    • Abstracting/ Indexing: EI (INSPEC, IET), DOAJ, Electronic Journals Library, Engineering & Technology Digital Library, Ulrich's Periodicals Directory, International Computer Science Digital Library (ICSDL), ProQuest and Google Scholar.
    • E-mail: lnse@ejournal.net
Editor-in-chief
Prof. Jemal Antidze
I. Vekua Scientific Institute of Applied Mathematics
Tbilisi State University, Georgia
I'm happy to take on the position of editor in chief of LNSE. We encourage authors to submit papers concerning any branch of Software Engineering.

LNSE 2013 Vol.1(2): 126-130 ISSN: 2301-3559
DOI: 10.7763/LNSE.2013.V1.28

Extraction and Classification of Twitter Messages to Apply in Business Intelligence

De La Cruz S. Carlos and Cortez H. Paola
Abstract—Nowadays the participation of users in information networks is increasing. Every day millions of people share opinions, experiences, modes through a comment, etc. However, this source of information called collective intelligence is unutilized at it is maximum capacity, because there comes a point where the user is oversaturated with so much information. The reason would be advisable to have the means to exploit the information that is expressed through the comments so that is synthesized and allow support to collective needs. This paper presents a way to exploit the information found within tweets of Twitter through programming language, ie applying data mining to the comments made. The aim is to show that through this language is simple start analyzing what the users say. The business intelligence system through social networks is proposed such as a case of study, which shows how they can be used in comments to support making decision. The Social Web has had a drive through the various websites that allow you to share information and which are known as social networking. The participation of users across these networks is astonishing; actually there are millions of people around the world who participates daily with at least one comment. But considering that a simple comment may contain relevant information, and joined the thousands of comments at a given time there is a source of collective information, synthesize that information would be important to support collective needs. This source of information can be manipulated in order to find patterns in the words that are used in the comments, and use them as benefits for the users.

Index Terms—Information networks, collective intelligence, twitter, business intelligence.

D. S. Carlos is with the Telematic Academy of Professional Interdisciplinary Unit in Engineering and Advanced Technologies of National Polytechnic Institute, Avenue Insituto Politecnico Nacional No. 2580 Barrio La Laguna Ticoman, Mexico City (e-mail: carlosdelac@gmail.com, cdelacruz@ipn.mx).
C. H. Paola is with the Informatica Academy of Professional Interdisciplinary Unit in Engineering and Advanced Technologies of National Polytechnic Institute, Avenue Insituto Politecnico Nacional No. 2580 Barrio La Laguna Ticoman, Mexico City (e-mail :pcortez@ipn.mx).

[PDF]

Cite: De La Cruz S. Carlos and Cortez H. Paola, "Extraction and Classification of Twitter Messages to Apply in Business Intelligence," Lecture Notes on Software Engineering vol. 1, no. 2, pp. 126-130, 2013.

Copyright © 2008-2015. Lecture Notes on Software Engineering. All rights reserved.
E-mail: lnse@ejournal.net