Naslov
Hot Topic Detection Using Twitter Streaming Data

Autori
Jagić, Teodor ; Brkić, Ljiljana

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO) / - : Institute of Electrical and Electronics Engineers (IEEE), 2020, 1730-1735

ISBN
978-1-7281-5339-1

Skup
43rd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2020) ; MIPRO junior - Student Papers (SP 2020)

Mjesto i datum
Opatija, Hrvatska, 28.09.2020. - 02.10.2020

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
hot topic detection , social networks , text analysis , geographic clustering

Sažetak
Ith the increasing popularity and widespread use of social networks, it is becoming increasingly beneficial to analyse the data being shared to identify topics of public interest and specific social phenomena. This paper analyses the possibilities, challenges and difficulties of automatic periodic collection and analysis of data from popular social networks and explains in detail the acquisition and analysis of data from Twitter. The paper explains an implementation of a simple hot topic detection algorithm based on texts acquired from the Twitter's official API. The texts collected are being pre-processed by removing stop-words and stemming the remaining words using Porter’s stemming algorithm. Words from pre-processed text are assigned ranks depending on a large-scale analysis using TF- IDF weight and grouped into a hot topic. The algorithm accuracy was evaluated by comparison with Twitter's official hot topic detection algorithm. Appropriate user interface enabling configuring the process of data acquisition, analysis and viewing results in a geographic fashion was implemented.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA