Measuring and profiling the topical influence and sentiment contagion of public event stakeholders

Luo, An; Ou, Menghua; Li, Gang; Yu, Chuanming; Wang, Xiaofen

doi:10.1016/j.ijinfomgt.2021.102327

Cited by 43 publications

(41 citation statements)

References 39 publications

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“…The public online negative sentiment during the COVID-19 pandemic had the most significant impact on the livestock product and vegetable prices in the spread period, followed by the outbreak period and the recession period, and the most significant impact on the aquatic product and fruit prices in the recession period, which rejected Hypothesis 3 . These results were similar to the conclusions in An et al (2021) , which found that the topic propagation was most influential in the recession phase and the sentiment propagation most influential in the spreading phase. While the public online negative sentiment was strongest during the outbreak period, the impact on agricultural prices was not the greatest.…”

Section: Resultssupporting

confidence: 90%

“…In the low-risk areas, this dynamic response was significantly higher in the recession period than in the other life cycle stages; therefore, Hypothesis 3 was rejected. These findings were similar to those in An et al (2021) , but not the same in Zeng et al (2019) . This was because the high-risk and medium-risk areas were the first to be affected by the pandemic ( Li et al, 2021 ) and the continuous fermentation of the online negative sentiment caused a public panic, which led to panic buying behaviors.…”

Section: Resultssupporting

confidence: 89%

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Dynamic impact of negative public sentiment on agricultural product prices during COVID-19

Liu

Tang

et al. 2022

Journal of Retailing and Consumer Services

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Section: Resultssupporting

confidence: 90%

Section: Resultssupporting

confidence: 89%

Dynamic impact of negative public sentiment on agricultural product prices during COVID-19

Liu

Tang

et al. 2022

Journal of Retailing and Consumer Services

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“…Among them, the topic out-degree was explained as the proportion of the same type of topic among all the nodes extending outward from the node in social networks built on the forwarding relationships. The emotion out-degree was interpreted as the proportion of the same type of emotion among all the nodes extending outward from the node in the social network formed by the construction of forwarding relationships [ 9 ]. The former mainly represents the influence caused by the spread of topics in social networks, while the latter mainly represents the influence caused by the spread of emotion in social networks.…”

Section: Methodsmentioning

confidence: 99%

“…When a public event occurs, the public quickly establishes a cooperative communication network through social media [ 8 ]. Through the realization of such functions as posting, commenting, and forwarding, a complex topic, and emotion communication network is constructed in a short time [ 9 ]. At the same time, social media is not only an important platform for the public to understand and exchange information related to the event and seek official explanation, but also an important means for the government to respond to social demands and calm the public emotion.…”

Section: Introductionmentioning

confidence: 99%

Topic-Emotion Propagation Mechanism of Public Emergencies in Social Networks

Cai

Luo

Xiao

et al. 2021

Sensors

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The information propagation of emergencies in social networks is often accompanied by the dissemination of the topic and emotion. As a virtual sensor of public emergencies, social networks have been widely used in data mining, knowledge discovery, and machine learning. From the perspective of network, this study aims to explore the topic and emotion propagation mechanism, as well as the interaction and communication relations of the public in social networks under four types of emergencies, including public health events, accidents and disasters, social security events, and natural disasters. Event topics were identified by Word2vec and K-means clustering. The biLSTM model was used to identify emotion in posts. The propagation maps of topic and emotion were presented visually on the network, and the synergistic relationship between topic and emotion propagation as well as the communication characteristics of multiple subjects were analyzed. The results show that there were similarities and differences in the propagation mechanism of topic and emotion in different types of emergencies. There was a positive correlation between topic and emotion of different types of users in social networks in emergencies. Users with a high level of topic influence were often accompanied by a high level of emotion appeal.

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“…Social media (SM) has provided an effective channel for the diffusion of multidimensional information of public emergencies (An, Zhou, Ou, Li, Yu, & Wang, 2021), which may amplify the impact of an emergency. In previous studies, the evolution paths of information on the public emergency were viewed from a decentralized perspective for every single component such as emotional or network information (Kim, Bae, & Hastak, 2018).…”

Section: Introductionmentioning

confidence: 99%

Interactive Evolution of Multidimensional Information in Social Media for Public Emergency: A Perspective from Optics Scattering

Xiao

2021

Data and Information Management

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Most of the current research on the information analysis of social media (SM) for public emergency focused on a single dimension such as emotion while neglecting the interaction between multidimensional information. Therefore, in this study, an information dispersing–superimposing model is proposed to explain the implicit regularity of the impact within a symbol, sentiment, and context information and their dependent evolution on the SM. Information hue, saturation, and flux (HSF) are defined to measure the interaction process. An online event was selected to verify the concept and hypothesis of this study. The results proved that the interaction among multidimensional information did exist on the SM for a public emergency. The turning points of information dispersing–superimposing often emerged when the number of online users involved had significant changes, and sentiment and context information were showed to have a strong interaction relationship and tended to be spread at the same time. It was also manifested that the dominant information component was varied at each stage of the emergency. This paper is one of the first to study the interaction of multidimensional information on the SM derived from optics scattering. The findings of the study will try to provide a theoretical explanation for why certain information components may be enhanced during the online dissemination and suggest practical support for the information predictions and interface design for SM.

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Measuring and profiling the topical influence and sentiment contagion of public event stakeholders

Cited by 43 publications

References 39 publications

Dynamic impact of negative public sentiment on agricultural product prices during COVID-19

Dynamic impact of negative public sentiment on agricultural product prices during COVID-19

Topic-Emotion Propagation Mechanism of Public Emergencies in Social Networks

Interactive Evolution of Multidimensional Information in Social Media for Public Emergency: A Perspective from Optics Scattering

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