The LNM Institute of Information Technology

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Nirmal Kumar Sivaraman

nirmal.sivaraman@lnmiit.ac.in

Date of joining:

Department:

Computer Science Engineering


Summary


Biography


Research Area

Social Network Analysis, Information Diffusion

Personal information

Name

Designation

Department

ORCID

Scopus_link

Website

Mr. Nirmal Kumar Sivaraman

Assistant Professor

Computer Science Engineering

Education

Degree/DiplomaInstitute/ OrganizationYearBranch/Specialization
1M.S. Master of ScienceIIIT - Bangalore2016Information Technology

Experience

Name of OrganizationPost/DesignationDuration FromDuration To
1Infosys LimitedSenior Member - Education and Research20082016

Publications

1Sivaraman, N. K., Baijal, S., & Muthiah, S. B., On the Usage of Epidemiologial Models to Model Information Diffusion Over Twitter, Social Network Analysis and Mining, May 2023
2Sivaraman, N. K., Tokala, J. R., Rupesh, R. S. C. V., & Muthiah, S. B, Event Detection in Twitter using Social Synchrony and Average Number of Common Friends. In 13th ACM Web Science Conference 2021 (pp. 115-119). JUN 2021, Event Detection in Twitter using Social Synchrony and Average Number of Common Friends. In 13th ACM Web Science Conference 2021 (pp. 115-119). JUN 2021 ,
3 Sivaraman, N, Exo-SIR: An Epidemiological Model to Quantify the Exogenous Information Diffusion and its Application to Detect Events. In 13th ACM Web Science Conference 2021 (pp. 145-146). JUN 2021, Exo-SIR: An Epidemiological Model to Quantify the Exogenous Information Diffusion and its Application to Detect Events. In 13th ACM Web Science Conference 2021 (pp. 145-146). JUN 2021,
4Sivaraman N.K., Agarwal V., Vekaria Y., Muthiah S.B. , A Metadata-Based Event Detection Method Using Temporal Herding Factor and Social Synchrony on Twitter Data. In: Cherfi S., Perini A., Nurcan S. (eds) Research Challenges in Information Science. RCIS 2021. Lecture Notes in Business Information Processing, vol 415. Springer, Cham. MAY 2021, A Metadata-Based Event Detection Method Using Temporal Herding Factor and Social Synchrony on Twitter Data. In: Cherfi S., Perini A., Nurcan S. (eds) Research Challenges in Information Science. RCIS 2021. Lecture Notes in Business Information Processing, vol 415. Springer, Cham. MAY 2021,