Social Media Sentiment Analysis On Twitter Datasets

Tiwari, Shikha; Verma, Anshika; Garg, Peeyush; Bansal, Deepika

doi:10.1109/icaccs48705.2020.9074208

Cited by 31 publications

(6 citation statements)

References 5 publications

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“…Specifically, the methodology used, which consists of multimodal and discursive analyses, can fall within the field of Social Signal Processing ( Vinciarelli et al, 2011 ) and of Sentic Computing ( Susanto et al, 2021 ). This effort has been applied also within the field of automatic signal detection, which recently have crossed both linguistic levels, as in the case of Sentiment Multimodal Analysis ( Tiwari et al, 2020 ), and other body channel detection (e.g., facial or vocal expressions and body postures) ( Soleymani et al, 2017 ). More in general, the recent remarkable development of the Affective Computing and the introduction of deep learning increased the development of more sophisticated systems ( Wadawadagi and Pagi, 2020 ) aimed at predicting and automatically detecting emotional patterns starting from multimodal input ( Morency et al, 2011 ; Poria et al, 2016 ; Chaturvedi et al, 2019 ; Yadav and Vishwakarma, 2019 ), with a real-time output ( Cambria et al, 2013 ; Tran and Cambria, 2018 ).…”

Section: Discussionmentioning

confidence: 99%

The Humble Charisma of a White-Dressed Man in a Desert Place: Pope Francis’ Communicative Style in the Covid-19 Pandemic

et al. 2021

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The context of deep uncertainty, fear, and “social distancing” characterizing the COVID-19 pandemic has led to a need for cultural anchorages and charismatic leaders who may conjointly and effectively support human beings, strengthen their identity, and empower social commitment. In this perspective, the charismatic leadership of Pope Francis, which is widely shared not only within the religious world, may play a crucial role in facing emergency with existential reasons and psychological resources. The general aim of this work is to shed light on the communicative features of the charismatic leadership of Pope Francis during the pandemic emergency; in order to better understand his effectiveness, we analyzed both the core issues and his multimodal body signals in the global TV event of the Universal Prayer with the Urbi et Orbi Blessing. The multimodal and discursive analyses of the homily enabled us to define the “humble” charisma of the Pope, which is based upon on authentic and informal presence, manifested emotional signals (and, in particular commotion) showing features of equity and familiarity. From a discursive point of view, the common and overarching affiliation is constructed through a multiple focus on the “we” pronoun, which is constructed through socio-epistemic rhetoric. The results show how this integrated methodological perspectives, which is multimodal and discursive, may offer meaningful pathways detection of effective and persuasive signals.

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Section: Discussionmentioning

confidence: 99%

The Humble Charisma of a White-Dressed Man in a Desert Place: Pope Francis’ Communicative Style in the Covid-19 Pandemic

et al. 2021

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“…The explosion of data on the Internet has drawn significant attention yet is underutilized by medical AI communities. Especially on social media, the activity of crowdsourcing, spontaneous, and interactive knowledge sharing has opened up many opportunities for data-hungry fields [32,[41][42][43]. As one of the largest public social networks, Twitter has become the most proactive community for pathologists [16].…”

Section: Discussionmentioning

confidence: 99%

Leveraging medical Twitter to build a visual–language foundation model for pathology AI

Huang

Bianchi

Yüksekgönül

et al. 2023

Preprint

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The lack of annotated publicly available medical images is a major barrier for innovations. At the same time, many de-identified images and much knowledge are shared by clinicians on public forums such as medical Twitter. Here we harness these crowd platforms to curate OpenPath, a large dataset of 208,414 pathology images paired with natural language descriptions. This is the largest public dataset for pathology images annotated with natural text. We demonstrate the value of this resource by developing PLIP, a multimodal AI with both image and text understanding, which is trained on OpenPath. PLIP achieves state-of-the-art zero-shot and transfer learning performances for classifying new pathology images across diverse tasks. Moreover, PLIP enables users to retrieve similar cases by either image or natural language search, greatly facilitating knowledge sharing. Our approach demonstrates that publicly shared medical information is a tremendous resource that can be harnessed to advance biomedical AI.

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“…Classification was performed using Support Vector Machine (SVM), Decision Tree (DT), and Random Forest (RF) algorithms, with DT achieving an accuracy of 99.3%. For future research, the evaluation of feature extraction methods for Twitter data can be further explored [15]. TERUN, a transliteration-based encoding method, was used to normalize Roman Urdu/Hindi text.…”

Section: Machine Learning Methodsmentioning

confidence: 99%

Sentiment Analysis of Roman Text: Challenges, Opportunities, and Future Directions

Malik,

Ghous,

Ali

et al. 2023

ijisct

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The rise of social media platforms has sparked significant interest among Natural Language Processing (NLP) researchers in Sentiment Analysis over the past few decades. Numerous studies have focused on analyzing the sentiment of different languages, including Urdu, which is widely spoken in South Asia and serves as the national language of Pakistan. While considerable research has been conducted on sentiment analysis using Machine Learning (ML), Deep Learning (DL), and other methods, Roman Urdu sentiment analysis holds equal importance. This paper presents a comprehensive analysis of existing literature on sentiment analysis of various languages, with a specific focus on Roman text and approaches such as ML, DL, and others. Additionally, the paper proposes new directions for future researchers in this field.

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Social Media Sentiment Analysis On Twitter Datasets

Cited by 31 publications

References 5 publications

The Humble Charisma of a White-Dressed Man in a Desert Place: Pope Francis’ Communicative Style in the Covid-19 Pandemic

The Humble Charisma of a White-Dressed Man in a Desert Place: Pope Francis’ Communicative Style in the Covid-19 Pandemic

Leveraging medical Twitter to build a visual–language foundation model for pathology AI

Sentiment Analysis of Roman Text: Challenges, Opportunities, and Future Directions

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