CCF B类期刊IPM专刊截稿信息1条

数据库管理与信息检索

Information Processing & Management

Special Issue on Mining Social Influence and Actionable Insights from Social Networks

全文截稿: 2018-10-15

影响因子: 3.444

CCF分类: B类

中科院JCR分区:

  • 大类 : 工程技术 - 3区

  • 小类 : 计算机：信息系统 - 3区

网址: http://www.journals.elsevier.com/information-processing-and-management/

We solicit original, unpublished and innovative research work on all aspects around, but not limited to, the following themes:

Predictive modeling based on social networks such as

o Box office prediction

o Election prediction

o Flu prediction

Product adaptation models with social networks such as

o Sale price prediction

o New product popularity prediction

o Brand popularity

o Business downfall prediction

User modeling and social networks including

o Predict users daily activities including recurring events

o User churn prediction

o Determining user similarities, trustworthiness and reliability

Social networks and information/knowledge dissemination

o Topic and trend prediction

o Prediction of information diffusion patterns

o Identification of causality and correlation between event/topics/communities

Social network analysis and measures

o Network topology

o Centrality measures

o Community detection

o Dynamic network models

o Diffusion models

Information diffusion modeling with social networks

o Information propagation and assimilation in social networks

o Sentiment diffusion in social networks

o Competitive intelligence from social networks

Social influence analysis on online social networks

o Systems and algorithms for discovering influential users

o Recommending influential users in online social networks

o Social influence maximization

o Modeling social networks and behavior for discovering influential users

o Discovering influencers for advertising and viral marketing in social networks

o Decision support systems and influencer discovering

Trust and reputation in social networks

Merging internal (proprietary) data with social data

Feature Engineering from Social Networks

Datasets and Evaluation methodologies for predictive modeling in social networks

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