A novel approach for visual data mining in Twitter micro-blogging platform. (2016)

• Record Type: Journal Article
• Authors: Maragoudakis, Manolis; Markou, Ioannis
• Is Part Of: International journal of social network mining. Volume 2:Number 3(2016)
• Page Start: 267
• Page End: 292
• Publication Date: 2016
• Subjects: data mining -- data visualisation -- textual data analysis -- sentiment analysis -- topic modelling -- social media -- Twitter -- data cleaning -- data reprocessing -- microblogging -- social networking -- social network analysis -- SNA -- knowledge discovery -- results readability; Online social networks -- Periodicals; Social networks -- Computer network resources -- Periodicals; Data mining -- Periodicals; 302.30285
• Languages: English
• ISSNs: 1757-8485

Abstract

In today's world of data dominance, social networking websites and especially micro-blogging platforms, form the largest share in current unstructured textual data. If the proper tools, such as sentiment analysis and topic modelling are applied to that data, valuable information would be produced. That information in turn could offer insights from understanding market trends to interpreting social phenomena. A question that comes to mind is: How can we use that information to enhance knowledge discovery and results readability? The answer is data visualisation. The purpose of this paper is to present a tool that was designed and developed to make use of network analysis algorithms in order to visualise social networking data. The goal of implementing this system is to create visual patterns from social media that leads to knowledge discovery and readable analysis results.