Fatemeh Abbasi’s research while affiliated with Ferdowsi University of Mashhad and other places

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Publications (1)


Influence maximization.
General dataset of influencers.
Some of images related to influencers in general dataset.
Some of images related to non-influencers in general dataset.
Topic-based dataset.

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Identifying Influentials in Social Networks
  • Article
  • Full-text available

January 2022

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111 Reads

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3 Citations

Fatemeh Abbasi

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In recent years, social networks have become very popular and an integral part of everyday life. People express their feelings and experiences in this virtual environment and become aware of others’ opinions and interests. Among them, influential users play an important role in disseminating information on social networks. Identifying such influencers is important in designing techniques to increase the speed of information dissemination. Such techniques are applicable in various fields including viral marketing, preventing the dissemination of harmful information, providing specialized recommendations, etc. Various approaches have been used to detect influencers on social networks, mostly based on the individual’s position in the network structure and their interactions. Considering the strengths and weaknesses of the previous methods, this study presents a novel method based on the content of the users’ posts without considering the network structure. This is done using a combination of high-level features extracted from images to measure the individual’s influence. Users’ images are investigated from three aspects: (1) color scheme, (2) advertising nature, (3) images’ semantics. To describe each of these aspects, feature extraction methods were used with acceptable accuracy in recognizing influential users. Finally, to achieve greater efficiency and precision, feature-combination methods have been investigated to provide an integrated classifier.

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Citations (1)


... An illustrative example of this concept is our ability to identify the most influential person within a social network. By doing so, we can gain insights into the reasons for their influence and how they manage to establish numerous connections with others (Abbasi & Fazl-Ersi, 2022). Furthermore, through analysis, researchers can forecast outcomes based on the accessible datasets, thus facilitating decision-making. ...

Reference:

Exploring Film Industry Dynamics: A Network Science Approach to Internet Movie Database Analysis
Identifying Influentials in Social Networks