Notice of Retraction The topology analyze of blogosphere through social network method

Cui, Yingan; Chen, Xiaogang; Xue, Li

doi:10.1109/icnc.2011.6022119

Cited by 3 publications

(3 citation statements)

References 10 publications

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Section: Social Network Datamentioning

confidence: 99%

“…Average path length is a concept in social network that is characterized as the normal number of steps along the shortest paths for all possible pairs of network vertices [11]. It is a proportion of the efficiency of information on a network [11]. The average or mean distance in a social network is defined as the average length of all shortest paths between all pairs of connected vertices in the graph.…”

Section: Social Network Datamentioning

confidence: 99%

See 1 more Smart Citation

A Comparative Study on Various Sharing Among Undergraduates in PreCovid-19 and Covid-19 Period Using Network Parameters

Deepa¹,

Lakshmanan

Sreeja³

2021

Intelligent Sustainable Systems

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Best way amongst other approach to analyze social-cultural-economicalemotional-intellectual components are by using the network parameters in social network analysis (SNA). Covid-19 is a staggering illness brought about by an as of late found coronavirus. This has totally changed the manner in which we approach life, particularly in propensities, working environment, public transportation framework, and not least the instructive framework. Institutional instructive framework offered approach to online training framework. Here, we studied various sharings such as intellectual, financial, emotional and information among undergraduates forming these relations as a directed graph. The concepts of density, reciprocity, geodesic distance etc. are used here to treat the directed graphs. The effects of gender, caste, locality, financial status and intelligent quotient level in this sharing are examined in these periods.

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Section: Social Network Datamentioning

confidence: 99%

Section: Social Network Datamentioning

confidence: 99%

A Comparative Study on Various Sharing Among Undergraduates in PreCovid-19 and Covid-19 Period Using Network Parameters

Deepa¹,

Lakshmanan

Sreeja³

2021

Intelligent Sustainable Systems

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show abstract

“…Similar work, using SNA on online social networks, was also carried out by [5] to detect opinion leaders and opinion trends, [7] to study the topology characteristics and features of blogosphere, [4] for ranking the most influential users on Twitter based on a combination of the user position in the network topology, the polarity of that user's opinions and the textual quality of the tweets, [9] to understand complex health networks in social media, and [17] to analyze a political blog community in order to find the core group members.…”

Section: Related Workmentioning

confidence: 99%

Identifying the Topic-Specific Influential Users and Opinion Leaders in Twitter

Shalaby¹,

Rafea

2013

Artificial Intelligence and Applications / 794: Modelling, Identification and Control / 795: Parallel and Distributed Computing

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The content in online communities has become strategically important that the identification of the influential members can benefit all in developing business opportunities, forging political agendas, discussing social and societal issues, and can lead to many interesting innovative applications. Among social networking websites, one of the most important is Twitter. We are interested in identifying the topic-specific influential members in Twitter. Influence of a user may be determined by many factors. The objective of the study is to identify the factors that play a crucial role in the measurement of a Twitter user's influence, examine how the different factors impact the influence ranking and how these factors can be expressed in a mathematical model. We devise a model to score the strength of a user's influence using basic user features collected for a group of users discussing a common issue. We then validate our results using Klout as a reference point, and then further verify our ranking of the users by manual evaluation.

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Identifying the Topic-Specific Influential Users in Twitter

Shalaby¹,

Rafea²

2018

IJCA

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Social Influence can be described as the ability to have an effect on the thoughts or actions of others. Influential members in online communities are becoming the new media to market products and sway opinions. Also, their guidance and recommendations can save some people the search time and assist their selective decision making. The objective of this research is to detect the influential users in a specific topic on Twitter. From a collection of tweets matching a specified query, the influential users are to be detected in an online fashion. In order to address this, the issue of which set of features can best lead us to the topic-specific influential users is investigated along with how these features can be expressed in a model to produce a list of ranked influential users.

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Notice of Retraction The topology analyze of blogosphere through social network method

Cited by 3 publications

References 10 publications

A Comparative Study on Various Sharing Among Undergraduates in PreCovid-19 and Covid-19 Period Using Network Parameters

A Comparative Study on Various Sharing Among Undergraduates in PreCovid-19 and Covid-19 Period Using Network Parameters

Identifying the Topic-Specific Influential Users and Opinion Leaders in Twitter

Identifying the Topic-Specific Influential Users in Twitter

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