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Open AccessArticle

SentiFlow: An Information Diffusion Process Discovery Based on Topic and Sentiment from Online Social Networks

Department of Industrial and Management Systems Engineering, Kyung Hee University, Yongin-si, Gyeonggi-do 446-701, Korea
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Sustainability 2018, 10(8), 2731; https://doi.org/10.3390/su10082731
Received: 3 July 2018 / Revised: 30 July 2018 / Accepted: 31 July 2018 / Published: 2 August 2018
(This article belongs to the Special Issue Big Data Research for Social Sciences and Social Impact)
In this digital era, people can become more interconnected as information spreads easily and quickly through online social media. The rapid growth of the social network services (SNS) increases the need for better methodologies for comprehending the semantics among the SNS users. This need motivated the proposal of a novel framework for understanding information diffusion process and the semantics of user comments, called SentiFlow. In this paper, we present a probabilistic approach to discover an information diffusion process based on an extended hidden Markov model (HMM) by analyzing the users and comments from posts on social media. A probabilistic dissemination of information among user communities is reflected after discovering topics and sentiments from the user comments. Specifically, the proposed method makes the groups of users based on their interaction on social networks using Louvain modularity from SNS logs. User comments are then analyzed to find different sentiments toward a subject such as news in social networks. Moreover, the proposed method is based on the latent Dirichlet allocation for topic discovery and the naïve Bayes classifier for sentiment analysis. Finally, an example using Facebook data demonstrates the practical value of SentiFlow in real world applications. View Full-Text
Keywords: information diffusion; community detection; topic analysis; sentiment analysis; social networks information diffusion; community detection; topic analysis; sentiment analysis; social networks
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Carrera, B.; Jung, J.-Y. SentiFlow: An Information Diffusion Process Discovery Based on Topic and Sentiment from Online Social Networks. Sustainability 2018, 10, 2731.

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