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Tweet2Sent: Web application for Visualizing Sentiment from Tweets (CROSBI ID 442212)

Ocjenski rad | sveučilišni preddiplomski završni rad

Kranjčević, Leon Tweet2Sent: Web application for Visualizing Sentiment from Tweets / Bagić Babac, Marina (mentor); Zagreb, Fakultet elektrotehnike i računarstva, . 2021

Podaci o odgovornosti

Kranjčević, Leon

Bagić Babac, Marina

engleski

Tweet2Sent: Web application for Visualizing Sentiment from Tweets

Online social network Twitter allows users to upload short text messages - tweets, and this restriction encourages users to construct focused, timely updates. From the perspective of text analysis, it remains a challenging task to estimate and visualize sentiment for such short and incomplete text snippets. The specific goal of this thesis is to develop a web application for tweet retrieval and visualization that presents sentiment and basic emotional properties embodied in the text. Sentiment from text should be estimated using lexicon-based methods.

sentiment analysis ; natural language processing ; stemming ; web scraping ; polarity ; subjectivity ; visualizing

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Podaci o izdanju

37

09.07.2021.

obranjeno

Podaci o ustanovi koja je dodijelila akademski stupanj

Fakultet elektrotehnike i računarstva

Zagreb

Povezanost rada

Računarstvo