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Home / Proceedings / Proceedings of the International AAAI Conference on Web and Social Media

Fusing Audio, Textual, and Visual Features for Sentiment Analysis of News Videos

February 1, 2023

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Authors

Moisés Pereira,Flávio Pádua,Adriano Pereira,Fabrício Benevenuto,Daniel Dalip

University Center of Belo Horizonte (UNI-BH).,Federal Center for Technological Education of Minas Gerais (CEFET-MG),Federal University of Minas Gerais (UFMG),Federal University of Minas Gerais (UFMG),University Center of Belo Horizonte (UNI-BH)


DOI:

10.1609/icwsm.v10i1.14810


Abstract:

This paper presents a novel approach to perform sentiment analysis of news videos, based on the fusion of audio, textual and visual clues extracted from their contents. The proposed approach aims at contributing to the semiodiscoursive study regarding the construction of the ethos (identity) of this media universe, which has become a central part of the modern-day lives of millions of people. To achieve this goal, we apply state-of-the-art computational methods for (1) automatic emotion recognition from facial expressions, (2) extraction of modulations in the participants' speeches and (3) sentiment analysis from the closed caption associated to the videos of interest. More specifically, we compute features, such as, visual intensities of recognized emotions, field sizes of participants, voicing probability, sound loudness, speech fundamental frequencies and the sentiment scores (polarities) from text sentences in the closed caption. Experimental results with a dataset containing 520 annotated news videos from three Brazilian and one American popular TV newscasts show that our approach achieves an accuracy of up to 84% in the sentiments (tension levels) classification task, thus demonstrating its high potential to be used by media analysts in several applications, especially, in the journalistic domain.

Topics: ICWSM

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HOW TO CITE:

Moisés Pereira,Flávio Pádua,Adriano Pereira,Fabrício Benevenuto,Daniel Dalip Fusing Audio, Textual, and Visual Features for Sentiment Analysis of News Videos Proceedings of the International AAAI Conference on Web and Social Media (2016) 659-662.

Moisés Pereira,Flávio Pádua,Adriano Pereira,Fabrício Benevenuto,Daniel Dalip Fusing Audio, Textual, and Visual Features for Sentiment Analysis of News Videos ICWSM 2016, 659-662.

Moisés Pereira,Flávio Pádua,Adriano Pereira,Fabrício Benevenuto,Daniel Dalip (2016). Fusing Audio, Textual, and Visual Features for Sentiment Analysis of News Videos. Proceedings of the International AAAI Conference on Web and Social Media, 659-662.

Moisés Pereira,Flávio Pádua,Adriano Pereira,Fabrício Benevenuto,Daniel Dalip. Fusing Audio, Textual, and Visual Features for Sentiment Analysis of News Videos. Proceedings of the International AAAI Conference on Web and Social Media 2016 p.659-662.

Moisés Pereira,Flávio Pádua,Adriano Pereira,Fabrício Benevenuto,Daniel Dalip. 2016. Fusing Audio, Textual, and Visual Features for Sentiment Analysis of News Videos. "Proceedings of the International AAAI Conference on Web and Social Media". 659-662.

Moisés Pereira,Flávio Pádua,Adriano Pereira,Fabrício Benevenuto,Daniel Dalip. (2016) "Fusing Audio, Textual, and Visual Features for Sentiment Analysis of News Videos", Proceedings of the International AAAI Conference on Web and Social Media, p.659-662

Moisés Pereira,Flávio Pádua,Adriano Pereira,Fabrício Benevenuto,Daniel Dalip, "Fusing Audio, Textual, and Visual Features for Sentiment Analysis of News Videos", ICWSM, p.659-662, 2016.

Moisés Pereira,Flávio Pádua,Adriano Pereira,Fabrício Benevenuto,Daniel Dalip. "Fusing Audio, Textual, and Visual Features for Sentiment Analysis of News Videos". Proceedings of the International AAAI Conference on Web and Social Media, 2016, p.659-662.

Moisés Pereira,Flávio Pádua,Adriano Pereira,Fabrício Benevenuto,Daniel Dalip. "Fusing Audio, Textual, and Visual Features for Sentiment Analysis of News Videos". Proceedings of the International AAAI Conference on Web and Social Media, (2016): 659-662.

Moisés Pereira,Flávio Pádua,Adriano Pereira,Fabrício Benevenuto,Daniel Dalip. Fusing Audio, Textual, and Visual Features for Sentiment Analysis of News Videos. ICWSM[Internet]. 2016[cited 2023]; 659-662.


ISSN: 2334-0770


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