Data Harvesting and Event Detection from Czech Twitter

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F18%3A43952961" target="_blank" >RIV/49777513:23520/18:43952961 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-319-93581-2_6" target="_blank" >http://dx.doi.org/10.1007/978-3-319-93581-2_6</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-93581-2_6" target="_blank" >10.1007/978-3-319-93581-2_6</a>

Result language

angličtina

Original language name

Data Harvesting and Event Detection from Czech Twitter

Original language description

Twitter belongs to the fastest-growing microblogging and online social media. Automatically monitoring and analyzing this rich and continuous data stream can yield valuable information, which enable users and organizations to discover important knowledge. This paper proposes a method for harvesting of important messages from Czech Twitter with high download speed and an approach to discover automatically the events in such data. We identified important Twitter users and then we use these lists to discover potentially interesting tweets to download. The tweets are then clustered in order to discover the events. Final decision is based on the thresholding. We show that the harvesting method downloads about 6 times more data than the other approaches. We further report promising results of the event detection approach on a small corpus of the Czech Tweets.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/LO1506" target="_blank" >LO1506: Sustainability support of the centre NTIS - New Technologies for the Information Society</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2018

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Agents and Artificial Intelligence

ISBN

978-3-319-93580-5

ISSN

0302-9743

e-ISSN

1611-3349

Number of pages

14

Pages from-to

102-115

Publisher name

SPRINGER

Place of publication

Cham

Event location

Porto, Portugal

Event date

Feb 24, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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