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SmartData Collective > Analytics > Text Analytics > Case Study : Competitive Intelligence for Telecommunications
Business IntelligenceText Analytics

Case Study : Competitive Intelligence for Telecommunications

ThemosKalafatis
ThemosKalafatis
3 Min Read
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Telcos are a good example of a fast moving business environment and a good candidate for using Competitive Intelligence analysis from Social Media sources.
Telcos are a good example of a fast moving business environment and a good candidate for using Competitive Intelligence analysis from Social Media sources. The Case Study involves three major Telcos located in an Eastern European Country and shows the results from the analysis of thousands of Tweets and FaceBook wall posts to understand the following :
– How subscribers perceive each Telco Brand? 
– Which information do subscribers tend to Re-Tweet and “Like” on FaceBook Wall Posts? 
– Which words and Topics are commonly found with Intense feelings / thoughts?
– Which topics are mostly discussed when subscribers compare two or more Telco operators?
– What do subscribers discuss about  Network Quality and Speed, Billing, Promotions, Marketing Events, Customer Care, TV Commercials etc.
– How do they prioritize these topics and which of them are interesting and why?  
– What do subscribers talk about in general (i.e without any Telco Brand being mentioned) regarding Internet speed, Charges and what would they expect to see more?
I will present the Case Study mentioned above in the forthcoming 9th Annual European Text Analytics Summit in April in London – UK. The Case Study is an example of application of Text Analytics to a language for which currently no tools exist and thus all difficulties and possible solutions will also be discussed. Examples will be also given on analyzing information to different conceptual levels and how this technique provides even more insights in consumer behavior.
The following tools were used for the analysis : 
– GATE to annotate all Topics that occur within Telco conversations (such as “sms”, “internet”, “dropped call”, “network”,”promotion”) and for setting up Conceptual Levels.
– R for pre-processing Text and performing Text Classification, Topic Detection and Cluster Analysis.
– WEKA  for Feature Selection and Text Classification.
– Finally,  Java is used to manage the information that is generated from GATE such as understanding how subscribers prioritize various Telco Concepts and Topics and also identify important phrases and/or words that frequently occur when these Topics are being discussed.  
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