Sentiment analysis and Opinion mining

This technology synthesizes the opinions at elementary level subsection (strongly negative opinion), and at higher levels (comment, document) and topics in order to provide a new entry point.

Target users and customers

Any organization that wants to qualify, follow and analyze the contents it manages or that is created on the Internet.

Application sectors

Monitoring of influence operations,
Fight against disinformation
Networks of opinion mapping,
E-reputation
Summary classification of consumer reviews,
Detection of positions on social networks
Make graphic analysis one the reviews to highlight the tendencies and the key concepts.
Analyze the consumer insight to better understand him.

Description:

Martine Garnier-Rizet Original Text:The rise of social media such as blogs and social networks has fueled interest in sentiment analysis. With the proliferation of reviews, ratings, recommendations and other forms of online expression, online opinion has turned into a kind of virtual currency for businesses willing to market their products, identify new opportunities and manage their reputations. As businesses tend to automate the process of filtering out the noise, understanding the conversations, identifying the relevant content, many are now looking into the field of sentiment analysis.

By investing in predictive analytics tools and other search solutions, businesses can gain valuable insights from their data and better serve the needs of their clients.

This technology synthesizes the opinions at elementary level subsection (strongly negative opinion), and at higher levels (comment, document) and topics in order to provide a new entry point.

The opinions are tagged with 3 pieces of information: 1/ The polarity; 2/ The intensity; 3/ A semantic category indicating the degree of involvement of the author.