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Document type:
Masterarbeit 
Author(s):
CHE, Lin 
Title:
Sentiment-based spatialtemporal event detection in social media data 
Abstract:
The emergence of social media provides a new source of sensing society. In this thesis, a novel event detection method for detecting real-world events based on population sentiment orientation (PSO) from social media check-in data is proposed. The method is mainly composed of sentiment analysis, spatial-temporal analysis, and event extraction. The hypothesis guiding this research is that social events change PSO in the dimension of time and space. The ratio of the number of positive and negativ...    »
 
Keywords:
Spatial-temporal analysis, Event detection, Social media, Sentiment analysis, Machine learning, Data mining 
Subject:
GEO Geowissenschaften 
DDC:
620 Ingenieurwissenschaften 
Advisor:
M.Sc. Juliane Cron, Ruoxin Zhu, TU München 
Referee:
Dr.-Ing. Eva Hauthal TU Dresden 
Year:
2019 
Quarter:
3. Quartal 
Year / month:
2019-09 
Month:
Sep 
Pages:
83 
Language:
en 
University:
Technische Universität München 
Faculty:
Ingenieurfakultät Bau Geo Umwelt 
TUM Institution:
Lehrstuhl für Kartographie 
End of processing:
11.09.2019