SciELO - Scientific Electronic Library Online

 
vol.23 número4Hindi Visual Genome: A Dataset for Multi-Modal English to Hindi Machine TranslationA Simple Multifractal Model for Self-Similar Traffic Flows in High-Speed Computer Networks índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

Links relacionados

  • No hay artículos similaresSimilares en SciELO

Compartir


Computación y Sistemas

versión On-line ISSN 2007-9737versión impresa ISSN 1405-5546

Resumen

ALATRISTA-SALAS, Hugo; CORDERO, Hugo  y  NUNEZ-DEL-PRADO, Miguel. PS I Love You: Privacy Aware Sentiment Classification. Comp. y Sist. [online]. 2019, vol.23, n.4, pp.1507-1515.  Epub 09-Ago-2021. ISSN 2007-9737.  https://doi.org/10.13053/cys-23-4-3296.

At first glance, one might think that people are aware of the availability of comments or posts on social networks. Therefore, one may believe that people do not share sensitive information on public social networks. Nonetheless, people's posts sometimes reveal susceptible information. These posts include mentions the use of drugs or alcohol, sexual preferences, intimate confessions and even serious medical conditions like cancer or HIV. Such privacy leaks could cost someone to get fired or even worse to be a victim of denial insurance or bad credit evaluations. In this paper, we propose a complete process to perform a privacy-preserving sentiment analysis trough Bloom filters. Our approach shows an accuracy difference between 1% and 3% less than their classic sentiment analysis task counter part while guarantying a private aware analysis.

Palabras llave : Privacy; sentiment analysis; disclosure risk; information loss; bloom filter.

        · texto en Inglés     · Inglés ( pdf )