Using eye-tracking data to create a weighted dictionary for sentiment analysis: the eye dictionary
Zammarchi, Gianpaolo
Methodology
;Antoch, Jaromir
2021-01-01
Abstract
Extracting information from written texts is of paramount importance to many entities (e.g. businesses, public organizations, individuals), but the exponential growth of available data has made this task beyond any single human being or business. Sentiment analysis is a tool to automatically transform the information extracted into knowledge. One of the main challenges is to assess if a text is positive or negative, which can be tackled using a dictionary where each word has a positive or negative associated value and then combining single-words values to express an overall text sentiment. In order to use such lexicon-based approach, we need an existing dictionary or to build a new one. In this work we present a new dictionary for sentiment analysis developed using eye-tracking data to determine the relevance of words and we assess its performances against other existing dictionaries.File | Size | Format | |
---|---|---|---|
CLADAG_2021_paper_80.pdf open access
Type: versione post-print
Size 154.4 kB
Format Adobe PDF
|
154.4 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.