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{{Abschlussarbeit
 
{{Abschlussarbeit
 
|Titel=Analyzing and Visualizing Twitter Streams based on Trending Hashtags
 
|Titel=Analyzing and Visualizing Twitter Streams based on Trending Hashtags
 +
|Vorname=Manuel
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|Nachname=Kaschura
 
|Abschlussarbeitstyp=Bachelor
 
|Abschlussarbeitstyp=Bachelor
 
|Betreuer=Mehwish Alam
 
|Betreuer=Mehwish Alam
 
|Partner=FIZ Karlsruhe
 
|Partner=FIZ Karlsruhe
 
|Forschungsgruppe=Information Service Engineering
 
|Forschungsgruppe=Information Service Engineering
|Abschlussarbeitsstatus=Offen
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|Abschlussarbeitsstatus=In Bearbeitung
 
|Beginn=2020/05/01
 
|Beginn=2020/05/01
|Ausschreibung=Analyzing and Visualizing Twitter Streams based on Trending Hashtags.pdf
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|Ausschreibung=Analyzing and Visualizing Twitter Streams based on Trending Hashtags_2.pdf
 
|Beschreibung DE=The objective of this thesis is to create a bot
 
|Beschreibung DE=The objective of this thesis is to create a bot
 
which analyzes the twitter streams. Each tweet should contain an ID, a location, time stamp, full text and URLs. The idea is to extract tweets from the current time up until 24 hours on some trending hashtag, e.g., #COVID19.
 
which analyzes the twitter streams. Each tweet should contain an ID, a location, time stamp, full text and URLs. The idea is to extract tweets from the current time up until 24 hours on some trending hashtag, e.g., #COVID19.

Aktuelle Version vom 4. Mai 2020, 13:11 Uhr



Analyzing and Visualizing Twitter Streams based on Trending Hashtags




Informationen zur Arbeit

Abschlussarbeitstyp: Bachelor
Betreuer: Mehwish Alam
Forschungsgruppe: Information Service Engineering
Partner: FIZ Karlsruhe
Archivierungsnummer: 4576
Abschlussarbeitsstatus: In Bearbeitung
Beginn: 01. Mai 2020
Abgabe: unbekannt

Weitere Informationen

The objective of this thesis is to create a bot which analyzes the twitter streams. Each tweet should contain an ID, a location, time stamp, full text and URLs. The idea is to extract tweets from the current time up until 24 hours on some trending hashtag, e.g., #COVID19. The second step is to perform sentiment analysis as well as emotion detection using existing tools. Finally, these generated sentiments and emotions should then be plotted on the globe visualizations based on location coordinates as provided by the location information in the tweet. It will only depict the sentiments of the population based on location about a current topic.


Ausschreibung: Download (pdf)