Bodor Almotairy; Manal Abdullah; Rabeeh Abbasi
Abstract
Entrepreneurship involves an immense network of activities, linked via collaborations and information propagation. Information dissemination is extremely important for entrepreneurs. Finding influential users with high levels of interaction and connectivity in social media and involving them in information ...
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Entrepreneurship involves an immense network of activities, linked via collaborations and information propagation. Information dissemination is extremely important for entrepreneurs. Finding influential users with high levels of interaction and connectivity in social media and involving them in information spread helps disseminating the information quickly. Thus, facilitating key entrepreneurial actors to find and collaborate with each other. Identifying and ranking entrepreneurial top influential people is still in infancy. This paper proposes an ERank framework for topic-specific influence theories that are specialized with respect to Twitter. Firstly, it extracts four dimensions to characterize influencers, including user popularity, activity, reliability, and tweet quality. Afterwards, it uses linear combinations of these dimensions to assign influence score to each user. Experimental results on a real-life dataset containing 233,018 Arabic tweets show that ERank successfully ranks 8 out of 10 entrepreneurial influencers. Unlike other existing approaches, ERank doesn’t require any labelled data and has lower computational cost. To ensure the effectiveness and efficiency of ERank, three validation techniques were used (1) to compare the detected influencers with the real-world influencers, (2) to investigate the spread of information of the detected influencers, and (3) to compare the quality of ERank results with other ranking methods.
Soran Ibrahim; Qing Tan
Abstract
In the recent years, social networks (SN) are now employed for communication and networking, socializing, marketing, as well as one’s daily life. Billions of people in the world are connected though various SN platforms and applications, which results in generating massive amount ...
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In the recent years, social networks (SN) are now employed for communication and networking, socializing, marketing, as well as one’s daily life. Billions of people in the world are connected though various SN platforms and applications, which results in generating massive amount of data online. This includes personal data or Personally Identifiable Information (PII). While more and more data are collected about users by different organizations and companies, privacy concerns on the SNs have become more and more prominent. In this paper, we present a study on information privacy in SNs through exploring the general laws and regulations on collecting, using and disclosure of information from Canadian perspectives based on the Personal Information Protection and Electronic Document Act (PIPEDA). The main focus of this paper is to present results from a survey and the findings of the survey.