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Microblogging during the European Floods 2013: What Twitter May Contribute in German Emergencies

Reuter, Christian ; Schröter, Julian (2023)
Microblogging during the European Floods 2013: What Twitter May Contribute in German Emergencies.
In: International Journal of Information Systems for Crisis Response and Management, 2015, 7 (1)
doi: 10.26083/tuprints-00022503
Artikel, Zweitveröffentlichung, Verlagsversion

Kurzbeschreibung (Abstract)

Social media is becoming more and more important in crisis management. However its analysis by emergency services still bears unaddressed challenges and the majority of studies focus on the use of social media in the USA. In this paper German tweets of the European Flood 2013 are therefore captured and analyzed using descriptive statistics, qualitative data coding, and computational algorithms. Our work illustrates that this event provided sufficient German traffic and geo-locations as well as enough original data (not derivative). However, up-to-date Named Entity Recognizer (NER) with German classifier could not recognize German rivers and highways satisfactorily. Furthermore our analysis revealed pragmatic (linguistic) barriers resulting from irony, wordplay, and ambiguity, as well as in retweet-behavior. To ease the analysis of data we suggest a retweet ratio, which is illustrated to be higher with important tweets and may help selecting tweets for mining. We argue that existing software has to be adapted and improved for German language characteristics, also to detect markedness, seriousness and truth

Typ des Eintrags: Artikel
Erschienen: 2023
Autor(en): Reuter, Christian ; Schröter, Julian
Art des Eintrags: Zweitveröffentlichung
Titel: Microblogging during the European Floods 2013: What Twitter May Contribute in German Emergencies
Sprache: Englisch
Publikationsjahr: 2023
Ort: Darmstadt
Publikationsdatum der Erstveröffentlichung: 2015
Verlag: IGI Global
Titel der Zeitschrift, Zeitung oder Schriftenreihe: International Journal of Information Systems for Crisis Response and Management
Jahrgang/Volume einer Zeitschrift: 7
(Heft-)Nummer: 1
DOI: 10.26083/tuprints-00022503
URL / URN: https://tuprints.ulb.tu-darmstadt.de/22503
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Herkunft: Zweitveröffentlichungsservice
Kurzbeschreibung (Abstract):

Social media is becoming more and more important in crisis management. However its analysis by emergency services still bears unaddressed challenges and the majority of studies focus on the use of social media in the USA. In this paper German tweets of the European Flood 2013 are therefore captured and analyzed using descriptive statistics, qualitative data coding, and computational algorithms. Our work illustrates that this event provided sufficient German traffic and geo-locations as well as enough original data (not derivative). However, up-to-date Named Entity Recognizer (NER) with German classifier could not recognize German rivers and highways satisfactorily. Furthermore our analysis revealed pragmatic (linguistic) barriers resulting from irony, wordplay, and ambiguity, as well as in retweet-behavior. To ease the analysis of data we suggest a retweet ratio, which is illustrated to be higher with important tweets and may help selecting tweets for mining. We argue that existing software has to be adapted and improved for German language characteristics, also to detect markedness, seriousness and truth

Freie Schlagworte: Computer-mediated communication, disaster management, emergency, data mining, text mining, social media, microblogging, Twitter, crisis informatics, entity extraction, information retrieval, clustering, web-based services, RapidMiner
Status: Verlagsversion
URN: urn:nbn:de:tuda-tuprints-225032
Sachgruppe der Dewey Dezimalklassifikatin (DDC): 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik
300 Sozialwissenschaften > 360 Soziale Probleme, Sozialdienste, Versicherungen
300 Sozialwissenschaften > 380 Handel, Kommunikation, Verkehr
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Wissenschaft und Technik für Frieden und Sicherheit (PEASEC)
Hinterlegungsdatum: 27 Feb 2023 11:06
Letzte Änderung: 06 Mär 2023 14:32
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