Image Analysis for Privacy Assessment in Social Networks

Taverner, Joaquin; Ruiz, Ramón Ceres; Val, Elena del; Diez, Carlos; Alemany, José

doi:10.1007/978-3-030-00524-5_1

Cited by 2 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To deal with this problem, research has made advances in the analysis and detection of properties in text and images from social networks (such as sentiment analysis, hate speech detection and private information detection) [2, 8,9,26]. Also, campaigns have been carried out to make people aware of the implications of sharing their data on social networks [15].…”

Section: Introductionmentioning

confidence: 99%

Detection and nudge-intervention on sensitive information in social networks

Alemany

Botti-Cebriá

Val

et al. 2022

Logic Journal of the IGPL

View full text Add to dashboard Cite

Detecting sensitive information considering privacy is a relevant issue on Online Social Networks (OSNs). It is often difficult for users to manage the privacy associated with their posts on social networks taking into account all the possible consequences. The aim of this work is to provide information about the sensitivity of the content of a publication when a user is going to share it in OSN. For this purpose, we developed a privacy-assistant agent that detects sensitive information. Based on this information, the agent provides a message through a nudge mechanism warning about the possible risks of sharing the message. To avoid being annoying, the agent also considers the user’s previous behaviour (e.g. if he previously ignored certain nudges) and adapts the messages it sends to give more relevance to those categories that are more important to the user from the point of view of the privacy risk. This agent was integrated into the social network Pesedia. We analysed the performance of different models to detect a set of sensitive categories (i.e. location, medical, drug/alcohol, emotion, personal attacks, stereotyping, family and association details, personal details and personally identifiable information) in a dataset of tweets in Spanish. The model that obtained the best results (i.e. F1 and accuracy) and that was finally integrated into the privacy-assistant agent was transformer-based.

show abstract

Section: Introductionmentioning

confidence: 99%

Detection and nudge-intervention on sensitive information in social networks

Alemany

Botti-Cebriá

Val

et al. 2022

Logic Journal of the IGPL

View full text Add to dashboard Cite

show abstract

“…In recent years, some proposals for assessing privacy on social networks have been made [1,4,29]. Most of these proposals involve the definition of metrics and mechanisms to improve trust and avoid the vulnerability of privacy in social networks [191,218]. One of these proposals is found in [9] in which Pesedia, a social network designed specifically to educate in the correct use of AGENT (SELECTED PAPER) social networks, is presented.…”

Section: Pesedia: a Pedagogical Social Networkmentioning

confidence: 99%

A BDI Empathic Agent Model Based on a Multidimensional Cross-Cultural Emotion Representation

Aparicio¹

View full text Add to dashboard Cite

Quisiera dar las gracias a mi familia por todo el cariño que me brinda, a mi pareja por soportarme durante todos estos años, tanto en los momentos buenos como en los no tan buenos, a mis amigos por animarme a seguir adelante, a los que caminaron a mi lado y ya no están, a mis directores Vicent y Emilio que, además de ser unos excelentes mentores, siempre me han apoyado ofreciéndome su consejo y mostrando una paciencia infinita incluso en los momentos de mayor debilidad y flaqueza. También quisiera agradecerles a mis compañeros de laboratorio y a mis compañeros del VRAIN por su apoyo y su colaboración y en especial a Bexy con la que compartí mis inicios en esta aventura.

show abstract

Image Analysis for Privacy Assessment in Social Networks

Cited by 2 publications

References 9 publications

Detection and nudge-intervention on sensitive information in social networks

Detection and nudge-intervention on sensitive information in social networks

A BDI Empathic Agent Model Based on a Multidimensional Cross-Cultural Emotion Representation

Contact Info

Product

Resources

About