An efficient approach to identify social disseminators for timely information diffusion

Lin, Lien Fa; Li, Yung-Ming

doi:10.1016/j.ins.2020.07.040

Cited by 28 publications

(5 citation statements)

References 32 publications

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“…The authors propose some measures in [22,23] to study the influence of neighboring nodes and those within a specific radius. Nevertheless, many real-world networks exhibit dynamic topological properties and structures that identify relevant information from important nodes.…”

Section: Related Workmentioning

confidence: 99%

Influential Yield Strength of Steel Materials with Return Random Walk Gravity Centrality

Rodríguez,

Curado,

Rodríguez

et al. 2024

Mathematics

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In complex networks, important nodes have a significant impact, both functional and structural. From the perspective of data flow pattern detection, the evaluation of the importance of a node in a network, taking into account the role it plays as a transition element in random paths between two other nodes, has important applications in many areas. Advances in complex networks and improved data generation are very important for the growth of computational materials science. The search for patterns of behavior of the elements that make up steels through complex networks can be very useful in understanding their mechanical properties. This work aims to study the influence of the connections between the elements of steel and the impact of these connections on their mechanical properties, more specifically on the yield strength. The patterns found in the results show the significance of the proposed approach for the development of new steel compositions.

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Section: Related Workmentioning

confidence: 99%

Influential Yield Strength of Steel Materials with Return Random Walk Gravity Centrality

Rodríguez,

Curado,

Rodríguez

et al. 2024

Mathematics

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“…The higher the influence of the users within a Weibo topic, the more people it affects and the greater the impetus to information dissemination. In the user interaction network, the more the number of other user nodes involved, the wider the population covered by the information is represented [ 28 ]. Hence, the user’s influence should be quantitatively defined from two perspectives: the user’s own influence and the user’s interaction behavior influence.…”

Section: Indicator System Establishment and Uwusrank Model Constructionmentioning

confidence: 99%

User Real-Time Influence Ranking Algorithm of Social Networks Considering Interactivity and Topicality

Piao

Sun

et al. 2023

Entropy

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At present, the existing influence evaluation algorithms often ignore network structure attributes, user interests and the time-varying propagation characteristics of influence. To address these issues, this work comprehensively discusses users’ own influence, weighted indicators, users’ interaction influence and the similarity between user interests and topics, thus proposing a dynamic user influence ranking algorithm called UWUSRank. First, we determine the user’s own basic influence based on their activity, authentication information and blog response. This improves the problem of poor objectivity of initial value on user influence evaluation when using PageRank to calculate user influence. Next, this paper mines users’ interaction influence by introducing the propagation network properties of Weibo (a Twitter-like service in China) information and scientifically quantifies the contribution value of followers’ influence to the users they follow according to different interaction influences, thereby solving the drawback of equal value transfer of followers’ influence. Additionally, we analyze the relevance of users’ personalized interest preferences and topic content and realize real-time monitoring of users’ influence at various time periods during the process of public opinion dissemination. Finally, we conduct experiments by extracting real Weibo topic data to verify the effectiveness of introducing each attribute of users’ own influence, interaction timeliness and interest similarity. Compared to TwitterRank, PageRank and FansRank, the results show that the UWUSRank algorithm improves the rationality of user ranking by 9.3%, 14.2%, and 16.7%, respectively, which proves the practicality of the UWUSRank algorithm. This approach can serve as a guide for research on user mining, information transmission methods, and public opinion tracking in social network-related areas.

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“…The massive adoption of social networks by users (especially professionals) is due to their ability to improve the efficiency of information sharing through collaborative filtering mechanisms for viral marketing recommendations and information dissemination techniques. Indeed, this information is disseminated from one node to another in a self-replicating manner, by sharing it with friends on the social network [9]- [12]. Friendly relationships between social users can result in significant variation in social networks, as users are influenced by their friends in decision-making [13].…”

Section: Literature Reviewmentioning

confidence: 99%

The impact of influencers on the companies reputation in developing countries: Case of Morocco

Chiny

Chihab

Juiher

et al. 2021

IJEECS

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With the emergence of social networks and their adoption by a large number of users, the importance of influencers continues to grow and companies are in a frantic race to recruit those most likely to promote their reputation and brand image. However, in the existing literature, there is little work that conducts quantitative studies on this subject in developing countries. For this reason, we conducted a study that attempts to understand the importance of influencers in reshaping public opinion of a company or brand. We chose as a subject of study a large Moroccan company operating in the telecommunications sector that hired a popular influencer among young Moroccans. We then adopted an approach based on scraping and analyzing the occurrences of the influencer's posts on Instagram and the content of the company's website and then publishing a questionnaire to 180 respondents in the age range of most of the followers of the influencer in question. The results suggest that a positive relationship exists between the influencer and brand reputation, meaning that if the person is following the influencer who has published content on the brand, that person is expected to be systematically aware of the brand, and vice versa.

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An efficient approach to identify social disseminators for timely information diffusion

Cited by 28 publications

References 32 publications

Influential Yield Strength of Steel Materials with Return Random Walk Gravity Centrality

Influential Yield Strength of Steel Materials with Return Random Walk Gravity Centrality

User Real-Time Influence Ranking Algorithm of Social Networks Considering Interactivity and Topicality

The impact of influencers on the companies reputation in developing countries: Case of Morocco

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