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Titel:

Spatially Supervised Text Mining for Social Media Cleaning and Preprocessing

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Werner, Martin
Abstract:
In this paper, we show a framework for partial bot rejection based on spatially supervised text mining from social media messages. We show qualitative results towards the reduction of known bots and give hints on how this cleaning technique can help us in filling gaps of current signals related to human life on Earth based on social media. The bot rejection framework is based on using a spatial signal for supervising a machine learning model with extreme label noise still being able to reject so...     »
Stichworte:
social media analysis, text mining, data cleaning
Zeitschriftentitel:
GI_Forum
Jahr:
2021
Band / Volume:
1
Seitenangaben Beitrag:
68-75
Volltext / DOI:
doi:10.1553/giscience2021_01_s68
Verlag / Institution:
Osterreichische Akademie der Wissenschaften
E-ISSN:
2308-17082308-1708
Publikationsdatum:
01.01.2021
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