Tweet2Sent: Web application for Visualizing Sentiment from Tweets (CROSBI ID 442212)
Ocjenski rad | sveučilišni preddiplomski završni rad
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
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
Podaci o izdanju
37
09.07.2021.
obranjeno
Podaci o ustanovi koja je dodijelila akademski stupanj
Fakultet elektrotehnike i računarstva
Zagreb