Ms. Sogand Dehghan | Social Network Analysis | Best Researcher Award

University Lecturer | K. N. Toosi University of Technology | Iran

Ms. Sogand Dehghan is a dedicated Data Analyst and IT Specialist with strong expertise in data mining, machine learning, text mining, social network analysis, and software development. She specializes in collecting, cleaning, and analyzing large-scale datasets to create insightful reports and dashboards that support organizational decision-making. Her work bridges academia and industry, with contributions spanning research, teaching, and practical implementation of data-driven solutions. She is particularly passionate about analyzing social media networks to align with organizational objectives and developing innovative tools that integrate analytics with business strategies.

Professional Profile

Scopus | Orcid | Googlescholar

Education

Ms. Dehghan earned her Master’s degree in Information Technology from K. N. Toosi University of Technology, where she conducted advanced research on social media user evaluation using machine learning techniques. She also holds a Bachelor’s degree in Information Technology from Payame Noor University. Her academic training has equipped her with a strong foundation in data visualization, machine learning, text mining, and database management, supported by proficiency in multiple programming and analytical tools.

Experience

Ms. Dehghan has served in both academic and industrial roles. In academia, she has worked as a Lecturer at the National Skills University, teaching advanced programming and mentoring students in data analytics. In the industrial sector, she has held positions as Data Analyst and Software Developer at GAM Arak Industry and Kherad Sanat Arvand, where she utilized tools such as Power BI, Python, SQL Server, and SSRS to develop interactive dashboards, predictive models, and enterprise applications. Her professional background demonstrates her ability to translate research concepts into scalable industry solutions.

Research Interests

Her research interests lie in credibility assessment of social network users, big data analytics, and text mining. She focuses on integrating heterogeneous data sources, such as social media profiles and scholarly databases, to assess user trustworthiness for organizational purposes. She also investigates emerging research trends in library and information science using text mining approaches, contributing to the identification of new and impactful academic domains.

Honors

Ms. Dehghan has been recognized for her innovative contributions to machine learning-based social media analysis and her ability to apply academic research in real-world industrial projects. Her research has been published in well-regarded, peer-reviewed journals and indexed in major databases such as Scopus, reflecting the impact and relevance of her work.

Top Noted Publications

The credibility assessment of Twitter/X users based on organizational objectives by heterogeneous resources in big data life cycle – 2 citations, Scopus index, 2025

The text mining approach to investigate active areas of library and information science and discover emerging topics – 1 citation, Scopus index, 2024

The main components of evaluating the credibility of users according to organizational goals in the life cycle of big data – 1 citation, Scopus index, 2023

Main components of user credibility assessment according to organizational goals in the big data – Scopus index

Conclusion

Ms. Sogand Dehghan exemplifies a professional who seamlessly integrates academic research excellence with industry-driven solutions. Her expertise in data analytics, software development, and social network analysis positions her as a valuable contributor to both research and practical innovation. Through her work, she has advanced the understanding of social media credibility assessment, big data life cycle management, and emerging trends in information science. With her continuous pursuit of impactful research and her ability to bridge theory with application, she is poised to make further significant contributions to the fields of data science and information technology.