An approach to sentiment analysis in Twitter using expert tweets and retweeting hierarchy

Apoorva, G; Vaishnav, Neelam R; Chowdary, E. Durga; Chandrasekhar, Uddagiri

doi:10.1109/microcom.2016.7522482

Cited by 4 publications

(2 citation statements)

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“…The results show that detection, extraction, and classification of emotions, feelings, and opinions are the main applications coded as private states analysis. This category records 33 techniques, algorithms, or methods for performing [125] (TSSE) Tweet Sentiment Score Estimator [104] (BM) Naive Bayes, Bayesian Logistic [126]; [127] (LSA) Latent Semantic Analysis [128] (LIWC) Linguistic Inquiry and Word Count [129]; [130]; [131] (SANT) Sociological Approach to handling Noisy and short Texts [132] (SC) Sarcasm (TPR) True Positive Ratio [92] (SVM) Support Vector Machine [92] (LRS) Linguistic Rules Sarcasm [133]; [124] (TC) Text Classification (SVM) Support Vector Machine [134]; [135] (ENS) Ensemble Classifiers [135]; [136] (LECM) Latent Event Category Model [137] (BM) Naive Bayes, Bayesian Logistic [137]; [138] (RF) Random Forest [139] (LR) Logistic Regression [140] (SE) Search (FL) Fuzzy Logic [141] (TF-IDF) Term Frecuency [142]; [143] (KB) Knowledge Base (ON) Ontologias [144]; [145]; [95]; [146]; [147] (SI) Social Influence (PN) Proximity Networks [102] (PR) Pagerank [113] (ST) Statistical techniques [100] (BM) Naive Bayes, Bayesian Logistic [111] (DF) Difussion (RM) Rumor Model [117] (BM) Naive Bayes, Bayesian Logistic [127] (ST) Statistical techniques [122] (VAM) Vector Autoregressive Model…”

Section: B Subjectivity Analysismentioning

confidence: 99%

Hybrid Onion Layered System for the Analysis of Collective Subjectivity in Social Networks

Moreno-Sandoval

Pomares-Quimbaya

2022

IEEE Access

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This research aims to analyze the Digital Social Networks (DSN) behavior, constructed from the network's relationships, interactions, and expressions of users' private states through collective subjectivity. For this purpose, an onion-ring system called COSSOL has been built in a case study for Twitter, following a hybrid approach to integrate Machine Learning classifiers and structural metrics from Computational Linguistics and Computational Sociology disciplines, respectively. The paper designs two experimentation scenarios divided into cases of collective subjectivity analysis for Colombia under different levels of communities' granularity. The first case validates the system by performing a cointegration test on the metrics of each construct for the onion rings' communities. The results show that some communities better propagate their subjective expressions against the disclosed topic when they have a higher network density and a common polarity. Moreover, the most stable communities in polarity towards a topic are those whose members are highly connected. Conversely, communities with a higher centrality index in a subset of members do not exhibit stability in collective subjectivity towards a topic disclosed in that community. The second case validates the model with a series of Social Network Analysis (SNA) metrics with a polarity layer to describe the second onion ring subcommunities and their temporal variation through community recalculation. The results show no polar distributions similar to the bimodal ones representing consensus in the values of the common Thinking Acting and Feeling (TAF) forms. In addition, general negative sentiment is identified for the ten most representative nodes of the subcommunities analyzed.

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Section: B Subjectivity Analysismentioning

confidence: 99%

Hybrid Onion Layered System for the Analysis of Collective Subjectivity in Social Networks

Moreno-Sandoval

Pomares-Quimbaya

2022

IEEE Access

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“…However, some highlight Twitter as a suitable medium for fostering social dialogue (Williams, Russell-Mayhew, Nutter, Arthur, & Kassan, 2018). Twitter is a rich source of data containing diverse views and perspectives from a wide range of individuals (Apoorva, Vaishnav, Chowdary, & Uddagiri, 2016). The simple presence of an open comment section on online media pages negatively influences the perception of the media's credibility (Conlin & Roberts, 2016;Prochazka, Weber, & Schweiger, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

Behind the Comments Section: The Ethics of Digital Native News Discussions

Parra

Ayerdi

Peña-Fernández

2020

MaC

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Initially offered as a digital public sphere forum, comments sections became the preferred democratic arena for gatekeepers to encourage their readers to engage in constructive dialogue about relevant issues. However, news sites require commenters to remain civil in their interactions, which led users to seek alternative ways of commenting on the news. This article explores in-depth the contents of a sample of 98,426 user-comments collected between February–March 2019 from three major Spanish digital native newspapers: ElDiario.es, ElEspañol.com, and ElConfidencial.com. The main goals were to analyze whether comments in news outlets are deliberative, to assess the quality of the debate that takes place in them, and to describe their specific features. Discourse ethics were explored to determine the discussions’ impact, the language used, the acceptance of arguments, and the recognition and civility of participants. Findings reveal that comments sections in news outlets do not have a dialogic nature and that the debates have a low-quality profile. Nonetheless, the degree of mutual respect in interaction is acceptable, with slightly observed levels of incivility. Finally, the data suggest that the focused comments are higher on social media and that memes and emojis represent a new form of digital discourse.

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Sentiment Analysis on Public Transportation Using Different Tools and Techniques: A Literature Review

Singh

Pareek

2022

Communications in Computer and Information Science

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An approach to sentiment analysis in Twitter using expert tweets and retweeting hierarchy

Cited by 4 publications

References 10 publications

Hybrid Onion Layered System for the Analysis of Collective Subjectivity in Social Networks

Hybrid Onion Layered System for the Analysis of Collective Subjectivity in Social Networks

Behind the Comments Section: The Ethics of Digital Native News Discussions

Sentiment Analysis on Public Transportation Using Different Tools and Techniques: A Literature Review

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