Multimodal Sentiment Analysis for Automatic Estimation of Polarity Tension of TV News in TV Newscasts Videos

Sentiment analysis in the Malay language has traditionally focused on text-based data. Malay is the native language of Malaysia and other surrounding countries. While text-based sentiment analysis has shown good performance, it often lacks accuracy due to the absence of the speaker's affective state and intentions, which can lead to misinterpretations. Multimodal sentiment analysis addresses these shortcomings and has demonstrated improved performance in various prediction tasks. Unfortunately, there has been little research in this area for the Malay language, due to a lack of corpus and baseline studies. This paper introduces a new Malay Multimodal Sentiment Corpus, ‘MyMSC’, with annotations at both the multimodal and unimodal text levels. It contains 1208 segments covering political and social topics. The corpus development processes are described in detail, along with the necessary guidelines and considerations. This paper proposes a CNN-based framework with a late fusion method as the baseline model. Experiments with the proposed model demonstrate that the multimodal approach (F1 score = 0.77) outperforms the unimodal approach (F1 score = 0.68), validating the contribution of multimodality to classification performance. The differences between the two types of annotations and their impact are further elaborated. The full corpus is available at https://github.com/serenaroseaini/MyMSC .

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Galileo, a data platform for viewing news on social networks

Ulloa

Mellado

Blaña-Romero

et al. 2022

EPI

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This article aims to introduce Galileo, a platform for extracting and organizing news media data on social networks. Galileo integrates publications made on the main social networks used in the information ecosystem, namely Facebook, Twitter, and Instagram. Currently, the system includes 97 media outlets from nine countries: Brazil, Chile, Germany, Japan, Mexico, South Korea, Spain, United Kingdom, and United States. Galileo uses a Twitter API and the service CrowdTangle to download Facebook and Instagram posts. This data is stored in a local database and can be accessed through a user-friendly interface, which allows for the analysis of different characteristics of the posts, such as their text, source popularity, and temporal dimension. Galileo is a tool for researchers interested in understanding news cycles and analyzing news content on social networks.

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Multimodal Sentiment Analysis for Automatic Estimation of Polarity Tension of TV News in TV Newscasts Videos

Cited by 5 publications

References 5 publications

An overview of Multimodal Sentiment Analysis research: Opportunities and Difficulties

An overview of Multimodal Sentiment Analysis research: Opportunities and Difficulties

Multimodal Sentiment Analysis for the Malay Language: New Corpus using CNN-based Framework

Galileo, a data platform for viewing news on social networks

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