Impact Analysis of Online Social Networks

Individual usage of social media is expected to have a growing impact on the corporate reputation of organisations. Influential users of social media can disseminate positive or negative information and opinions about products, services, brands or businesses among members of their online networks in the social media spaces. The impact of such actions can often be substantial; negative information and opinions posted in social networks, blogs, online communities and forums has the potential to reach large numbers of people and substantially impact on the organisation's image and reputation. It is important for organisations to identify the online influencers -customers with important social networking impact -and identify ways to interact with them in order to respond efficiently to bad publicity or customer attacks. This study, based on extensive literature review and experts panel study based on the Delphi method, we construct a model identifying the social media influencers and the impact of these influencers on the corporate reputation.

Ijca Proceedings on Amrita International Conference of Women in Computing 2013, 2013

The World Wide Web is one of the most inevitable notions in the life of mankind. In the most recent times of the world it is much more in advance gaining popularity due to its enormous amount of capability in making the life more impact-able. Online social networks are one of the areas of the World Wide Web where people congregate to share and be part of the various virtual communities. Online social networks are more fascinating to many of us now as they look out for similarly inclined people in order to share in reciprocity their findings, ideals, thoughts, opinions and views. Much like the physical human networks, cybernetics too has people who can influence or influenced by the other. Some are leaders who inevitably influence voluminous people, while others look out to get influenced or to induce inspiration from their leader. Identifying people who exercise maximum influence could be useful in targeting them for marketing, knowledge dissemination and other such purposes. In this paper, we present empirical analysis of levels of influence in the online social network. Findings of this paper may be of great help to elucidate in ascertaining leaders of a social network which in turn can be used to sight the leaders in real world. The leaders of a social network are traced by using Pareto front function. We believe that this is the first study to use Pareto front function to identify the leaders in online social networks. The empirical results prove that the number of leaders in each subsequent level monotonically increase while the number of their followers decreases.

Proceedings of the 15th IPRRC

This research-in-progress seeks to uncover a deeper understanding of how influence works online, and how we might measure influence beyond the outputs and outtakes. In this literature review, several salient themes emerge: * Influence explained via social impact and opinion leadership o Mixed results on both accounts *Influence applied by a group on its individual members o By and large, literature supports this principle o Social identification with the group leads to being influenced by its members * Influence as a consequence of position in a social network o Two researchers did the same experiment and got different results. One study finds that influence rises according to position, but influence wanes as the scale of the network increases

IFIP Advances in Information and Communication Technology, 2014

This paper describes a methodology for rating the influence of a Twitter account in this famous microblogging service. Then it is evaluated over real accounts, under the belief that influence is not only a matter of quantity (amount of followers), but also a mixture of quality measures that reflect interaction, awareness, and visibility in the social sphere. The authors of this paper have created "InfluenceTracker", a publicly available website 1 where anyone can rate and compare the recent activity of any Twitter account.

International Journal of Advanced Research in Computer Science, 2018

Social Media had acquired a large popularity and user-ship. The social media had impacted users directly or indirectly in many ways. It has both positive and negative effects on the users. The users are of varying age groups and from different social and cultural backgrounds. Due to its vast usage and popularity among the people, the scholars have a keen interest on analyzing the impacts caused by social media. This review tries to focus on different existing articles and works which employed various data mining and statistical techniques to find the impact caused by social media. It mainly focuses on the impact of social media on variables such as society, education, student’s community, cybercrime, and security.

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022

In this paper, we present a methodology both informal community construction and strength of impact between people advance continually, it expects to follow the powerful hubs under a unique setting. To resolve this issue, we investigate the Influential Node Tracking (INT) issue as an expansion to the conventional Influence Maximization issue (IM) under powerful interpersonal organizations. While Influence Maximization issue targets distinguishing a bunch of k hubs to boost the joint impact under one static organization, INT issue centers around following a bunch of persuasive hubs that continues to expand the impact as the organization advances. Using the perfection of the advancement of the organization structure, we propose a productive calculation, Upper Bound Interchange Greedy (UBI) and a variation, UBI+. Rather than developing the seed set from the beginning, begin from the compelling seed set we find beforehand and execute hub substitution to further develop the impact inclusion. Moreover, by utilizing a quick update technique by working out the minor addition of hubs, our calculation can scale to dynamic interpersonal organizations with a huge number of hubs. Exact examinations on three genuine huge scope dynamic informal communities show that our UBI and its variations, UBI+ accomplishes better execution with regards to both impact inclusion and running time.

Intelligent Information and Database Systems, 2021

Social networks are increasingly proving to be the core of today's web. Identifying the influence on social networks is an area of research that presents many open issues. The challenge is finding ways that can effectively calculate and classify users according to criteria that suit them closer to reality. In this paper, we proposed a new method for measuring user influence on social networks. The influence of a user measures by taking into account the activity and the popularity of the user. We use Twitter as a case study for our method. Experiments show that our method achieves promising results in comparison to other methods.

Individual usage of social media is expected to have a growing impact on the corporate reputation of organisations. Influential users of social media can disseminate positive or negative information and opinions about products, services, brands or businesses among members of their online networks in the social media spaces. The impact of such actions can often be substantial; negative information and opinions posted in social networks, blogs, online communities and forums has the potential to reach large numbers of people and substantially impact on the organisation's image and reputation. It is important for organisations to identify the online influencers – customers with important social networking impact – and identify ways to interact with them in order to respond efficiently to bad publicity or customer attacks. This study, based on extensive literature review and experts panel study based on the Delphi method, we construct a model identifying the social media influencers and the impact of these influencers on the corporate reputation. Biographical notes: Wouter Vollenbroek is Researcher in the field of social media communication and reputation at the Faculty of Communication Studies at the University of Twente. Related interests are: social media innovation, social media behaviour and social media measurement. Other field of expertise are co-creation as a collaborative learning and designing method within on-and offline channels. His current research topic focuses on the question how we can understand the development, implementation and use of these co-creation processes and what factors contribute to the effects of these processes. His research is in the field of design and implementation of networked communication, learning networks, and learning organisations. He is interested in the roles and values of new media in these contexts. He is involved in national and international projects concerning knowledge networks, communities of practice, and virtual projects.

Web Ecology Project, http://tinyurl. com/ …, 2009

The Web Ecology Project is an interdisciplinary research group based in Boston, Massachusetts focusing on using large scale data mining to analyze the system-wide flows of culture and community online. In addition to the task of understanding culture on the web through quantitative research and rigorous experimentation, we are attempting to build a science around community management and social media. To that end, we are building tools and conducting research that enable planners to launch data-driven campaigns backed by network science.