News

The article "Transfer Learning with Social Media Content in the Ride-Hailing Domain by Using a Hybrid Machine Learning Architecture", by Álvaro de Pablo, Oscar Araque, and Carlos A. Iglesias has been published in the Electronics journal (2.397 impact factor, JCR Q3 2020). This work is a product of the Cabify-UPM Chair (Cátedra Cabify-UPM))

The full paper can be found at this URL.

 

Abstract:

The analysis of the content of posts written on social media has established an important line of research in recent years. The study of these texts, as well as their relationship with each other and their dependence on the platform on which they are written, enables the behavior analysis of users and their opinions with respect to different domains. In this work, a hybrid machine learning-based system has been developed to classify texts using topic modeling techniques and different word-vector representations, as well as traditional text representations. The system has been trained with ride-hailing posts extracted from Reddit, showing promising performance. Then, the generated models have been tested with data extracted from other sources such as Twitter and Google Play, classifying these texts without retraining any models and thus performing Transfer Learning. The obtained results show that our proposed architecture is effective when performing Transfer Learning from data-rich domains and applying them to other sources.

 

El 20 de Diciembre de 2021, por Resolución del Rector de la Universidad Politécnica de Madrid, se ha premiado al Profesor Óscar Araque con el Premio al Artículo Científico más citado de una Tesis Doctoral desarrollada y defendida en la UPM en su edición 2021. El artículo por el cual se ha recibido el galardón es "Enhancing deep learning sentiment analysis with ensemble techniques in social applications", publicado en la revista Expert Systems with Applications (JCR Q1 2017, 3.768), y forma parte de la tesis de Óscar Araque.

A día de hoy, esta publicación tiene:

On 26/11/2021 the awards for the best doctoral theses and master's theses awarded by the Colegio Oficial de Ingenieros de Telecomunicación (COIT) in 2020 and 2021 were presented. In this edition two members of the GSI have been awarded:

    - Mr. Óscar Araque, ISDEFE Awards for the Best Doctoral Thesis in Security and Defense.
    - D. Diego Benito, IN-NOVA Award for the Best Master's Thesis in Applications and Services for Cyber Defense and Cyber Intelligence.


 

Óscar Araque Iborra, Profesor de la Universidad Politécnica de Madrid y miembro del Grupo de Sistemas Inteligentes, ha recibido el Premio ISDEFE a la Mejor Tesis Doctoral en Seguridad y Defensa, concedido por el COIT. Este premio se concede a su Tesis titulada "A Distributional Semantics Perspective of Lexical Resources for Affect Analysis: An application to Extremist Narratives", presentada en la Universidad Politécnica de Madrid, con una calificación de Sobresaliente Cum Laude. La Tesis se encuentra accesible en el Archivo Digital UPM.

Esta tesis ha sido avalada ante el COIT por D. Enrique Vázquez Gallo, Director del Departamento de Ingeniería de Sistemas Telemáticos en la Escuela Técnica Superior de Ingenieros de Telecomunicación de la Universidad Politécnica de Madrid.

Participation in SALLD-1 Workshop on Sentiment Analysis & Linguistic Linked Data hold  held in conjunction with LDK 2021 – 3rd Conference on Language, Data and Knowledge in Zaragoza.

The invited talk is titled "Sentiment Analysis meets Linguistic Linked Data: An overview of the state-of-the-art". More  information at https://www.salld.org/schedule/