Analyzing tweets that mention the Sharing Economy

Within the last couple of years, the phenomenon of the Sharing Economy has gained momentum while companies like uber, airbnb, and blablacar have received 10-figure valuations. Within this thesis project the spotlight is on social media where people express opinions regarding the Sharing Economy. In order to conduct a (sentiment) analysis, tweets with certain hashtags need to be selected and analyzed. A perceivable strategy would be to analyze different domains (e.g. sharing of rides or apartments) and find out what people (dislike about them. For instance, people will be annoyed by uber drivers who are late or by apartments that do not comply with the description on the corresponding, i.e. airbnb. These opinions allow for the derivation of valuable information such as people's requirements, aversions, and intrinsic motivations.

Basically, this thesis is all about applying Natural Language Processing (NLP) techniques to tweets and to derive information about usage paterns, annoyances, and other (possibly hidden) insights.

Requirements

• Interest in social media, especially twitter
• Interest in Natural Language Processing (NLP)
• Some experience in programming, preferrably Java or Python