Buscar en RiuNet

Listar

Todo RiuNet

Mi cuenta

Acceder

Ayuda RiuNet

Admin. UPV

Listar por autor "Hernández Farias, Delia Irazu"

Mostrando ítems 1-9 de 9

A Knowledge-Based Weighted KNN for Detecting Irony in Twitter

Hernandez-Farias, Delia Irazu; Montes Gomez, Manuel; Escalante, Hugo; Rosso, Paolo; Patti, Viviana (Springer-Verlag, 2018)

[EN] In this work, we propose a variant of a well-known instancebased algorithm: WKNN. Our idea is to exploit task-dependent features in order to calculate the weight of the instances according to a novel paradigm: the ...
A survey on author profiling, deception, and irony detection for the Arabic language

Rosso, Paolo; Rangel-Pardo, Francisco Manuel; Hernandez-Farias, Delia Irazu; Cagnina, Leticia; Zaghouani, Wajdi; Charfi, Anis (Wiley, 2018-04)

[EN] The possibility of knowing people traits on the basis of what they write is a field of growing interest named author profiling. To infer a user's gender, age, native language, language variety, or even when the user ...
Applying basic features from sentiment analysis on automatic irony detection

Hernández Farías, Irazú; Benedí Ruiz, José Miguel; Rosso, Paolo (Springer International Publishing, 2015-06-09)

People use social media to express their opinions. Often linguistic devices such as irony are used. From the sentiment analysis perspective such utterances represent a challenge being a polarity reversor (usually from ...
Figurative Messages and Affect in Twitter: Differences Between #irony, #sarcasm and #not

Sulis, Emilio; Hernandez-Farias, Delia Irazu; Rosso, Paolo; Patti, Viviana; Ruffo, Giancarlo (Elsevier, 2016-09-15)

The use of irony and sarcasm has been proven to be a pervasive phenomenon in social media posing a challenge to sentiment analysis systems. Such devices, in fact, can influence and twist the polarity of an utterance in ...
Irony and Sarcasm Detection in Twitter: The Role of Affective Content

Hernández Farias, Delia Irazu (Universitat Politècnica de València, 2017-11-06)

Social media platforms, like Twitter, offer a face-saving ability that allows users to express themselves employing figurative language devices such as irony to achieve different communication purposes. Dealing with such ...
Irony Detection in Twitter with Imbalanced Class Distributions

Hernandez-Farias, Delia Irazu; Prati, Ronaldo; Herrera, Francisco; Rosso, Paolo (IOS Press, 2020)

[EN] Irony detection is a not trivial problem and can help to improve natural language processing tasks as sentiment analysis. When dealing with social media data in real scenarios, an important issue to address is data ...
Irony Detection in Twitter: The Role of Affective Content

Hernandez-Farias, Delia Irazu; Patti, Viviana; Rosso, Paolo (Association for Computing Machinery (ACM), 2016-08)

[EN] Irony has been proven to be pervasive in social media, posing a challenge to sentiment analysis systems. It is a creative linguistic phenomenon where affect-related aspects play a key role. In this work, we address ...
Multilingual Stance Detection in Social Media Political Debates

Lai, Mirko; Cignarella, Alessandra Teresa; Hernandez-Farias, Delia Irazu; Bosco, Cristina; Patti, Viviana; Rosso, Paolo (Elsevier, 2020-09)

[EN] Stance Detection is the task of automatically determining whether the author of a text is in favor, against, or neutral towards a given target. In this paper we investigate the portability of tools performing this ...
Web Service SWePT: A Hybrid Opinion Mining Approach

Baca-Gomez, Yolanda Raquel; Martínez, Alicia; Rosso, Paolo; Estrada Esquivel, Hugo; Hernandez-Farias, Delia Irazu (Graz University of Technology, Institut für Information systems und Computer Medien (IICM), 2016)

[EN] The increasing use of social networks and online sites where people can express their opinions has created a growing interest in Opinion Mining. One of the main tasks of Opinion Mining is to determine whether an ...