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Social Sentiment Analysis: Get trained by the SSIX project

26-10-2017

Social Sentiment Analysis: Get trained by the SSIX project

What is the aim? To analyse and understand social media users' attitudes for any given topic.

Why? These sentiment characteristics can be exploited to help SME’s operate more efficiently resulting in increased revenues.

For example, using SSIX, people’s engagement and opinion regarding products, companies, political candidates, etc. can be followed and evaluated in real time.

How? SSIX is searching and indexing conversations taking place on social network services, such as Twitter, StockTwits and Facebook.

Join us! The training workshop includes the following sessions:

09:00 - 10:50 Introduction to GATE
10:50 - 11:10 Coffee Break
11:10 - 13:00 GATE for sentiment analysis
13:00 - 14:00 Lunch
14:00 - 14:45 Use case: Possibilities and limits of political analyses
14:45 - 15:45 Deep learning, data driven semantics, INDRA
15:45 - 16:00 Coffee Break
16:00 - 16:40 Aspect extraction and machine learning approaches
16:40 - 17:40 Analysis techniques and its applications in the SSIX project
17:40 - 18:00 Networking opportunity

All training topics focus on how a tool is applied within SSIX, thereby ensuring real-life experience and application.

Participation: FREE of charge

Supported by:

Location

Euractiv Network Office
Boulevard Charlemagne 1, 1041 Brussels

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Panellists

Brian Davis, Lecturer, Department of Computer Science, Maynooth University
Gopal Sridhar, Researcher, Insight Centre for Data Analytics, NUI Galway
Jan Kleibrink, Senior Economist, Handelsblatt Research Institute
Siamak Barzegar, Researcher, University of Passau
Thomas Gaillat, Researcher, Insight Centre for Data Analytics, NUI Galway

Schedule

09:00 - 10:50 Introduction to GATE
10:50 - 11:10 Coffee Break
11:10 - 13:00 GATE for sentiment analysis
13:00 - 14:00 Lunch
14:00 - 14:45 Use case: Possibilities and limits of political analyses
14:45 - 15:45 Deep learning, data driven semantics, INDRA
15:45 - 16:00 Coffee Break
16:00 - 16:40 Aspect extraction and machine learning approaches
16:40 - 17:40 Analysis techniques and its applications in the SSIX project
17:40 - 18:00 Networking opportunity