Social intelligence framework: Extracting and analyzing opinions for social CRM

The increasing number of people using social media to express their personal experiences has led to an emerging interest in supporting social media analysis for marketing, opinion analysis and understanding community cohesion. Social customer relationship management (SCRM) systems have become an int...

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Bibliographic Details
Main Authors: Ennaji, Fatima Zohra, El Fazziki, Abdelaziz, Sadgal, Mohamed, Benslimane, Djamal
Format: Conference Proceeding
Language:English
Subjects:
Big Data
Blogs
Communities
Computer architecture
Computers
Conferences
Consolidation
Customer relationship management
Digital media
Electronics
Filtering
Hadoop
Intelligence
Organizations
Reliability
Sentiment analysis
Social CRM
Social network services
Social networks
Twitter
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Summary:The increasing number of people using social media to express their personal experiences has led to an emerging interest in supporting social media analysis for marketing, opinion analysis and understanding community cohesion. Social customer relationship management (SCRM) systems have become an interesting research area. Generally analysis needs to be done on large volumes of data (Big Data) in an efficient and timely manner. In this research, we propose a social intelligence framework that can extract and consolidate the reviews expressed via social media to help enterprises to know more about the customers' opinion toward the target products. This goal can be achieved by analyzing the reviewers' knowledge and authority and their opinion, sentiment (SentiGem) toward the target products, after filtering the extracted tweets from Twitter using Twitter4J. Additionally we present an architecture based on Map/Reduce analysis using Hadoop.
ISSN:2161-5330
DOI:10.1109/AICCSA.2015.7507229