Int. J. of Big Data Intelligence   »   2017 Vol.4, No.1

 

 

Title: A knowledge-based integrated framework for increasing social management intelligence

 

Authors: George Dimitrakopoulos; Vassilis Chatzigiannakis; Leonidas Tsitouras

 

Addresses:
Department of Informatics and Telematics, Harokopio University of Athens, 9 Omirou str., 17778, Athens, Greece
Department of Informatics and Telematics, Harokopio University of Athens, 9 Omirou str., 17778, Athens, Greece
Department of Informatics and Telematics, Harokopio University of Athens, 9 Omirou str., 17778, Athens, Greece

 

Abstract: The internet and the social media in particular, have been playing an increasingly vital role in everyday people's communication. This has resulted in a tremendous shift of investments by corporate marketing departments, focusing on social media and digital marketing solutions versus traditional media. Despite the abundance of social media marketing solutions, there is no concrete framework on how to actually listen to people interacting in social media and to use these insights to perform and monitor marketing campaigns. Furthermore, monitoring such campaigns' impact on public opinion and decisions through social media channels, and assisting companies accelerate their growth accordingly with novel integrated tools and strategies has been an unexplored field. In this respect, this paper presents an integrated platform, capable of: a) aggregating at real time huge amounts of data from social media and online publications; b) intelligently processing this data through sophisticated sentiment analysis algorithms; c) proposing novel structured approaches for the exploitation of these data through applying technologically innovative and efficient marketing practices. Indicative use cases prove the effectiveness of the proposed platforms.

 

Keywords: big data analysis; social media; marketing; integrated platform; sentiment analysis; social management intelligence; data aggregation; online publications.

 

DOI: 10.1504/IJBDI.2016.10002003

 

Int. J. of Big Data Intelligence, 2017 Vol.4, No.1, pp.36 - 46

 

Available online: 26 Dec 2016

 

 

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