Human context in Sentiment Analysis symbolic technique
Amo-Filvà, Daniel (La Salle-Universitat Ramón Llull)
Usart Rodriguez, Mireia (Universitat Rovira i Virgili)
Grimalt Álvaro, Carme (Universitat Rovira i Virgili)
Chen, Jiahui (La Salle-Universitat Ramón Llull)

Fecha:	2022
Descripción:	9 pàg.
Resumen:	Learning methodologies in Virtual Learning Environments that encourage students' written communication require additional effort from the trainers, in terms of management and sentimental awareness of both, the group and each participant. Analysing and evaluating sentiment for every message in every conversation is a hard and tedious work. This is one of the reasons why Natural Language Processing (NLP) and Sentiment Analysis (SA) are gaining popularity. The idea of automating the processes of emotional evaluation of students' conversations in an academic context invites us to consider those automatisms as substitutes for manual processes, such as SA. The challenge of including the human context, together with treating the data with adequate privacy in terms of current legislation, makes these techniques complex. There are two main techniques in SA, those based on lexicons and those based on machine learning. In the present study, results of SA based on two different lexicons, are compared with the results of a manual labelling performed by human trainers to test the effectiveness of the SA technique. Regarding the privacy concerns, an open-source local analysis tool was updated and incorporated such automated processes, both for the present study and for trainers to use considering the extracted results. The results show that lexical-based SA processes tend to consider messages towards the extremes (positive/negative), while human beings' evaluation tends towards sentimental neutrality, both in female and male.
Ayudas:	La Caixa Foundation LCF/PR/SR19/52540001
Nota:	Proceedings of the Learning Analytics Summer Institute Spain (LASI Spain) 2022, June 20-21, 2022, Salamanca, Spain
Derechos:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Lengua:	Anglès
Documento:	Article ; recerca ; Versió publicada
Materia:	Sentiment analysis ; Natural language processing ; Word list ; Human context
Publicado en:	CEUR workshop proceedings, Vol. 3238 (2022) , p. 61-69, ISSN 1613-0073

Adreça alternativa: http://ceur-ws.org/Vol-3238/paper9.pdf

9 p, 3.2 MB

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