Discovering patterns in social media conversations

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label Diverse autorenew 2025-09-29, 17:01 history_edu Silviu Marinescu
Currently people are increasingly using social media environments to communicate and have conversations about products and services they use. These conversations represent valuable information for companies providing insight about what elements of a product and service could be improved.

Furthermore, this information is relevant because it has an enormous impact on the purchase behavior and brand attitudes from other customers. However analyzing this information and acting on it is hard due to the high volumes of data and the unstructured characteristics of textual information. With an expected market potential of $978 million by 2014 (Forrester Research 2009), opinion mining research is advanced to deal with the measurement and analysis of online conversations. Opinion mining models have been designed in order to allow firms sensing market opinion about their product and services through sentiment metrics.

These metrics allow companies to understand what's the overall opinion (positive or negative) about determined product and services and its characteristics.Across this course students' understanding about the opportunities that textual information offers for research and business purposes will be expanded. Students will learn about the characteristics of textual information, the different platforms that provide this data, and the implications for research.

Later, opinion (text) mining techniques will be studied at a basic level to provide the students an understanding of the methods for analysing large volumes of textual data. Strengths and weaknesses of this methods will be discussed with real examples from online conversations about product and service reviews.

Period
05-08-2013 - 16-08-2013 (2 weeks)

Target group
Students in economics or business.

Course aim
Learning objectives of this course:



1) Understanding that textual information contained in social media environments (Facebook, Twitter, Amazon, and others) is a valuable source for research and business purposes.

2) Provide students with a basic knowledge of opinion (text) mining methods and tools to carry out research on large volumes of data.

3) Provide students with an overall criteria to assess their results, interpret them and provide research and business reports.

Credits
4.0 ECTS credits

Course fee
EUR 700: Course + course materials

Course leader
Francisco Villarroel Ordenes, Phd Marketing and Supply Chain Management

Scholarships
Not available

Maastricht University + Maastricht School of Management Student Service Centre
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