Online ISSN: 2515-8260

Keywords : Social networks

The Growth Of Social Media In The Last Decade.

Nishu Singh,Anamika Singh,Pranjhal Sonwani,Anchal Shukla,Ms. Shinki K Pandey .

European Journal of Molecular & Clinical Medicine, 2023, Volume 10, Issue 1, Pages 687-696

Social media comprises communication websites that facilitate relationship forming between users from di- verse backgrounds, resulting in a rich social structure. User generated content encourages inquiry and decision-making. Given the relevance of social media to various stakeholders, it has received significant attention from researchers of various fields, including information systems. There exists no comprehensive review that integrates and synthesizes the findings of literature on social media. This study discusses the findings of 132 papers (in selected IS journals) on social media and social networking published between 1997 and 2017. Most papers reviewed here examine the behavioral side of social media, investigate the aspect of reviews and recommendations, and study its integration for organization- al purposes. Furthermore, many studies have investigated the viability of online communities/social media as a marketing medium, while others have explored various aspects of social media, including the risks associated with its use, the value that it creates, and the negative stigma attached to it within workplaces. The use of social media for information sharing during critical events as well as for seeking and/ or rendering help has also been investigated in prior re- search. Other contexts include political and public administration, and the comparison between traditional and social media. Overall, our study identifies multiple emergent themes in the existing corpus, thereby furthering our under- standing of advances in social media research. The integrated view of the extant literature that our study presents can help avoid duplication by future researchers, whilst offering fruitful lines of enquiry to help shape research for this emerging field.

Detection and Identification of Bogus Profiles in online Social Network using Machine Learning Methods


European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 395-400

Here current creation online social networks (OSNs) become more and more common and the social life of people has become more linked to these pages. They use OSNs to remain in finger with everyone else, distribute news, prepare dealings and still run their personal e-. Out of control of the OSN's evolution and the huge extent of their supporters 'individual developments, they have been attackers and impostors who take individual information, share fake news and disseminate vindictive exercises. Researchers in various fields began inspecting environmentally friendly techniques in order to perform abnormal activity and counterfeit money that is based on accounting and classification algorithms [1]. However, the use of stand-alone classification algorithms no longer yields a straightforward outcome, some of the factors that are manipulated by the account have a low influence or have no impact in the closing results. The paper proposes to use the SVM-NN as a modern algorithm to effectively identify suspected Twitter accounts and bots, to add four choices and to restrict measurements. Three laptop classification mastering algorithms were used to determine the actual or false identity of target accounts. They included the SVM, the Neural Network and our recently urbanized SVM-NN method that utilizes far less hardware but is still able to correctly identify about 98% of the money due to the training data set.


Moulishree .; Vishnu Priya; K. R. Don; R. Gayathri

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 1, Pages 2155-2172

Social networks are seen as a group of internet based technology. It provides a platform to share contents, interest and develop new skills and personalities in the virtual world . The definition for this depends from person to person. There are no boundaries to the use of social networks. The aim of the study is to determine the attitude towards social networks among different age groups. A well structured questionnaire enclosed with closed ended questions was prepared which was surveyed among 100 active participants . The data collected is analysed in SPSS software version 22 by descriptive analysis. The questionnaire is administered to the participants to online google forms link.There exists a positive attitude towards social networks among all age groups. Awareness on advantages and disadvantages of the social networks should be inculcated in the minds of the younger generation.