O2 Repositori UOC
Coneixement obert per transformar el món
Enviaments recents
Large scale analysis of gender bias and sexism in song lyrics
(Springer Open, 2023-04-20) Betti, Lorenzo; Abrate, Carlo; Kästner, Andreas
We employ Natural Language Processing techniques to analyse 377,808 English song
lyrics from the “Two Million Song Database” corpus, focusing on the expression of
sexism across five decades (1960–2010) and the measurement of gender biases.
Using a sexism classifier, we identify sexist lyrics at a larger scale than previous studies
using small samples of manually annotated popular songs. Furthermore, we reveal
gender biases by measuring associations in word embeddings learned on song lyrics.
We find sexist content to increase across time, especially from male artists and for
popular songs appearing in Billboard charts. Songs are also shown to contain different
language biases depending on the gender of the performer, with male solo artist
songs containing more and stronger biases. This is the first large scale analysis of this
type, giving insights into language usage in such an influential part of popular culture.
Sharing emotions at scale: The Vent dataset
(AAAI Conference on Web and Social Media, 2019-03-24) Lykousas, Nikolaos; Patsakis, Constantinos; Kaltenbrunner, Andreas; Gómez, Vicenç
The continuous and increasing use of social media has en-
abled the expression of human thoughts, opinions, and every-
day actions publicly at an unprecedented scale. We present
the Vent dataset, the largest annotated dataset of text, emo-
tions, and social connections to date. It comprises more than
33 millions of posts by nearly a million users together with
their social connections. Each post has an associated emotion.
There are 705 different emotions, organized in 63 “emotion
categories”, forming a two-level taxonomy of affects. Our ini-
tial statistical analysis describes the global patterns of activ-
ity in the Vent platform, revealing large heterogeneities and
certainly remarkable regularities regarding the use of the dif-
ferent emotions. We focus on the aggregated use of emotions,
the temporal activity, and the social network of users, and
outline possible methods to infer emotion networks based on
the user activity. We also analyze the text and describe the
affective landscape of Vent, finding agreements with existing
(small scale) annotated corpus in terms of emotion categories
and positive/negative valences. Finally, we discuss possible
research questions that can be addressed from this unique
dataset.
Edició i correcció del text II, setembre 2019
(Universitat Oberta de Catalunya (UOC), 2019-09) Ferran Neira, Alicia
Recurs d’aprenentatge de la Universitat Oberta de Catalunya.
Auditor de qualitat. Implantació SGC, septiembre 2019
(Universitat Oberta de Catalunya (UOC), 2019-09) GONZALEZ CAMBRAY, RAMON; Jiménez Creis, Pere; López Soriano, José
Recurs d’aprenentatge de la Universitat Oberta de Catalunya.
Planificación estratégica y gestión de la comunicación interna, septiembre 2019
(Universitat Oberta de Catalunya (UOC), 2019-09) Pineda Munné, Marina; GONZALEZ CAMBRAY, RAMON
Recurs d’aprenentatge de la Universitat Oberta de Catalunya.