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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Event based analysis in social network using the approaches of machine learning |
| Authors Name: | Naga Hari Babu , Swapna Vanguru , Bhavani Vanama |
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IJNRD_204938
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| Published Paper Id: | IJNRD2309110 |
| Published In: | Volume 8 Issue 9, September-2023 |
| DOI: | |
| Abstract: | Abstract : The importance of machine learning for social network analysis is realized as an inevitable tool in forthcoming years. This is due to the rapid growth of data in social network, increased by the proliferation of social media websites and the embedded heterogeneity and complexity. In recent times, Social Network Analysis has become a very important and interesting subject matter with regard to Artificial Intelligence in that a vast variety of processes, comprising animate and inanimate entities, can be examined by means of SNA. In this regard, SNA has been employed by security agencies for counter-intelligence and law enforcement purposes. SNA has been used in medicine and pharmaceuticals for gaining insights into protein-protein interactions. Also, SNA has been employed in the World Wide Web (WWW) for hyperlink analysis, cyber society analysis, sentiment analysis, etc. Furthermore, prediction tasks within social network structures have become significant research problems in SNA. Thus, hidden facts and details embedded in social network structures can be effectively and efficiently harnessed for training AI models with the goal of predicting several missing components (such as links/ties, nodes/actors, structure type, etc.) within a given social network. Therefore, important factors such as the individual attributes of spatial social actors, and the underlying patterns of relationship binding these social actors must be taken into consideration; because these factors are 1 relevant in understanding the nature and dynamics of a given social network structure. SNA is a subdomain (or research topic) within the domain (or research area) of AI; and several open problems still exist with regard to SNA. Some of these open problems with respect to SNA are included . This paper proposes two important things. 1) the various approaches which dealt by machine learning with concern to deep learning viz: Information Diffusion, Community Detection, Event-Based Analysis, Multi-Layer Network Analysis, Trends and Patterns Analyses, Sentiment Analysis, Collaboration and Knowledge Management, Node Classification, Link Detection, Breakup Prediction, etc. Thus, in this dissertation, we have proposed effective Machine Learning (ML) approaches toward resolving the following SNA (research) problems, namely: Breakup Prediction, Link Prediction, Node Classification, Event-based Analysis, and Trend/Pattern Analysis. 2) Analysing the Event based analysis in social network using the approaches of machine learning. |
| Keywords: | Keywords: Social Networks, Machine learning, Clustering, Classification, WWW |
| Cite Article: | "Event based analysis in social network using the approaches of machine learning", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 9, page no.b97-b105, September-2023, Available :http://www.ijnrd.org/papers/IJNRD2309110.pdf |
| Downloads: | 000118752 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2309110 Registration ID: 204938 Published In: Volume 8 Issue 9, September-2023 DOI (Digital Object Identifier): Page No: b97-b105 Country: Medchal, Telanagana, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2309110 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2309110 |
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