Journal Press India^®

Author Details ( * ) denotes Corresponding author

The utilization of crowd-sourced opinions by policy makers presents a difficult task in terms of managing information and ensuring authenticity. Information retrieval and handling extensive link-intensive applications across widely distributed in the social network. Social media facilitates the information diffusion to the community and supporting online community development. In order to establish a transparent decision-making process, strategies are effectively filter the insights derived from the crowd-sourced opinions It is a significant challenge within the realm of social networks; therefore, policy makers must ensure that they avoid being influenced by biased sources when making decisions. The detection of communities can be achieved through link prediction algorithms, which can also aid in understanding how information propagates within social network structures. Ego-centric nodes play an essential role in disseminating information and serve as an efficient method for selecting a opinion of nodes within the network.

Keywords

Social Media, Crowdsourcing, Recommender Systems, Decision Making, Link Prediction algorithm

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