Mining Twitter Features for Event Summarization and Rating
Document Type
Conference Proceeding
Publication Date
2017
DOI
https://doi.org/10.1145/3106426.3106487
Abstract
We present CEST, a generic method for detection and rich summarization of events occurring in a city. CEST exploits Twitter metadata, does not need prior information on events, and is event category and structure agnostic. We developed CEST to process unstructured documents and take advantage of shorthand notations, hashtags, keywords, geographical and temporal data, as well as sentiment within tweets to both detect and summarize arbitrary events without prior knowledge. We also introduce a novel strategy that analyzes sentiment and tweeting behavior over time to create a qualitative score that captures events' overall appeal to attendees.
Publication Information
Mallela, Deepa; Ahlers, Dirk; and Pera, Maria Soledad. (2017). "Mining Twitter Features for Event Summarization and Rating". WI '17: Proceedings of the International Conference on Web Intelligence, 615-622.