Titlebook: Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining; Nitin Agarwal,Nima Dokoohaki,Serpil To

Communal

Deepak Kakadia,Jin Yang,Alexander Gilgurcontinuously increasing volume of data exchanged between those users, it is reasonable to think of methods to improve information accuracy and also protect users’ privacy. In this research we proposed a weighted-based approach to describe relations between users in OSNs. Users in OSNs interact with

sacrum

leniency

神刊

Network Radar Countermeasure Systems,ccounts readily generate Big Data marked by velocity, volume, value, variety, and veracity challenges. This type of Big Data analytics already supports useful investigations ranging from research into data mining and developing public policy to actions targeting an individual in a variety of domains

沒(méi)收

Customer Relationship Management,ersification of platforms, from crowdsourcing ones, social computing platforms (in terms of collaborative task execution), and online labor/expert markets to collective adaptive systems (CAS) with humans-in-the-loop. Despite the advancements in various mechanisms to support effective provisioning of

Nebulous

就職

Privacy in Human Computation: User Awareness Study, Implications for Existing Platforms, Recommendatecting mechanisms, we conducted an online survey study to assess user privacy awareness in human computation systems and in this paper provide the results of it. Lastly, we provide recommendations for developers for designing privacy-preserving human computation platforms as well as research directions.

Cubicle

STEER

Predictive Analysis on Twitter: Techniques and Applications, approaches, and state-of-the-art applications of predictive analysis of Twitter data. Specifically, we present fine-grained analysis involving aspects such as sentiment, emotion, and the use of domain knowledge in the coarse-grained analysis of Twitter data for making decisions and taking actions, and relate a few success stories.

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