Titlebook: Network Intelligence Meets User Centered Social Media Networks; Reda Alhajj,H. Ulrich Hoppe,Przemyslaw Kazienko Book 2018 Springer Interna

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書目名稱Network Intelligence Meets User Centered Social Media Networks影響因子(影響力)




書目名稱Network Intelligence Meets User Centered Social Media Networks影響因子(影響力)學科排名




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書目名稱Network Intelligence Meets User Centered Social Media Networks網絡公開度學科排名




書目名稱Network Intelligence Meets User Centered Social Media Networks被引頻次




書目名稱Network Intelligence Meets User Centered Social Media Networks被引頻次學科排名




書目名稱Network Intelligence Meets User Centered Social Media Networks年度引用




書目名稱Network Intelligence Meets User Centered Social Media Networks年度引用學科排名




書目名稱Network Intelligence Meets User Centered Social Media Networks讀者反饋




書目名稱Network Intelligence Meets User Centered Social Media Networks讀者反饋學科排名

persistence

Process-Driven Betweenness Centrality Measures in a social network. Borgatti states that almost all centrality measures assume that there exists a process moving through the network from node to node (Borgatti, Soc Netw 27(1):55–71, 2005). A node is then considered as central if it is important with respect to the underlying process. One often

去世

Behavior-Based Relevance Estimation for Social Networks Interaction Relationsd to make predictions about who will be friends as well as who is going to interact with each other in the future. Approaches incorporated in this prediction problem are mainly focusing on the amount or probability of interaction to compute an answer. Rather than characterizing an edge by the amount

亞當心理陰影

Network Patterns of Direct and Indirect Reciprocity in edX MOOC Forumsators advance learning analytics research of social relations in online settings, as they enable to compare interactions in different courses. Proposed indicators were derived through exponential random graph modelling (ERGM) to the networks of regular posters in four MOOC forums. Modelling demonstr

Audiometry

Extracting the Main Path of Historic Events from Wikipediacan make it easy to get lost in detail and difficult to gain a good overview of a topic. As a solution we propose a procedure to extract, summarize, and visualize large categories of historic Wikipedia articles. At the heart of this procedure we apply the method of main path analysis—originally deve

期滿

朝圣者

Community Aliveness: Discovering Interaction Decay Patterns in Online Social Communitiesmics of the interaction among the members of OSCs is not always growth dynamics. Instead, a . or . dynamics often happens, which makes an OSC obsolete. Understanding the behavior and the characteristics of the members of an inactive community helps to sustain the growth dynamics of these communities

Processes

Extended Feature-Driven Graph Model for Social Media Networksdels have been proposed to represent real social graphs to an acceptable extent. This enables researchers to try and evaluate new methods on a large number of social media networks. The work described here aims to introduce an extended feature-driven model that provides synthetic graphs that are suf

embolus

Incremental Learning in Dynamic Networks for Node Classificationlti-class classification of nodes’ states that varies over time and depends on information spread in the network. Demonstration of the method is conducted using social network dataset. According to sent messages between nodes, the emotional state of the message sender updates each receiving node’s f

Trigger-Point