Do Scientists Need Social Networks for Scientists?

2019 ◽  
Vol 56 (4) ◽  
pp. 37-42
Author(s):  
Evgeny V. Maslanov ◽  

The article analyzes the functioning of social networks for scientists on the Internet. The Internet has emerged as a social network for scientists. Then its development led to the formation of various network segments not related to scientific knowledge. It was based on the normative ideal of science. In the process of development, the Internet began to unite not only scientists. The normative ideal began to penetrate into network segments that were not directly associated to the activities of scientists. The development of the network has led to the formation of special social networks for scientists. However, as shown in the paper, such networks are not able to serve the basis either for the solidarity of scientists, or the formation of a new sociality of scientists, since the development of science has led to the formation of studies that cannot be represented in such networks. Scientists are better use general, not specialized, Internet social networks. In such communicative spaces, they can better deal with the tasks related to the communications with other social actors.

2013 ◽  
Vol 8 (1.) ◽  
Author(s):  
Slavica Vrsaljko ◽  
Tea Ljubimir

SMS messaging and communicating on social networks are increasingly widespread forms of informal communication. Mobile phones have almost all, and in addition they open profiles on the Internet social network, corresponding in this way with their peers. In writing messages is being recorded a large number of spelling errors, most of errors are those whose adoption is foreseen in the the lower grades of elementary school. In order to determine the level of mastery of linguistic norms, the message will be analysed as well as comments from the social networks of fourth-grade students.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Nauman Ali Khan ◽  
Wuyang Zhou ◽  
Mudassar Ali Khan ◽  
Ahmad Almogren ◽  
Ikram Ud Din

Social Internet of Things (SIoT) is a variation of social networks that adopt the property of peer-to-peer networks, in which connections between the things and social actors are automatically established. SIoT is a part of various organizations that inherit the social interaction, and these organizations include industries, institutions, and other establishments. Triadic closure and homophily are the most commonly used measures to investigate social networks’ formation and nature, where both measures are used exclusively or with statistical models. The triadic closure patterns are mapped for actors’ communication behavior over a location-based social network, affecting the homophily. In this study, we investigate triads emergence in homophilic social networks. This evaluation is based on the empirical review of triads within social networks (SNs) formed on Big Data. We utilized a large location-based dataset for an in-depth analysis, the Chinese telecommunication-based anonymized call detail records (CDRs). Two other openly available datasets, Brightkite and Gowalla, were also studied. We identified and proposed three social triad classes in a homophilic network to feature the correlation between social triads and homophily. The study opened a promising research direction that relates the variation of homophily based on closure triads nature. The homophilic triads are further categorized into transitive and intransitive groups. As our concluding research objective, we examined the relative triadic throughput within a location-based social network for the given datasets. The research study attains significant results highlighting the positive connection between homophily and a specific social triad class.


2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Gesu Li ◽  
Zhipeng Cai ◽  
Guisheng Yin ◽  
Zaobo He ◽  
Madhuri Siddula

The recommender system is mainly used in the e-commerce platform. With the development of the Internet, social networks and e-commerce networks have broken each other’s boundaries. Users also post information about their favorite movies or books on social networks. With the enhancement of people’s privacy awareness, the personal information of many users released publicly is limited. In the absence of items rating and knowing some user information, we propose a novel recommendation method. This method provides a list of recommendations for target attributes based on community detection and known user attributes and links. Considering the recommendation list and published user information that may be exploited by the attacker to infer other sensitive information of users and threaten users’ privacy, we propose the CDAI (Infer Attributes based on Community Detection) method, which finds a balance between utility and privacy and provides users with safer recommendations.


Author(s):  
M. L. Merani ◽  
M. Capetta ◽  
D. Saladino

Today some of the most popular and successful applications over the Internet are based on Peer-to-Peer (P2P) solutions. Online Social Networks (OSN) represent a stunning phenomenon too, involving communities of unprecedented size, whose members organize their relationships on the basis of social or professional friendship. This work deals with a P2P video streaming platform and focuses on the performance improvements that can be granted to those P2P nodes that are also members of a social network. The underpinning idea is that OSN friends (and friends of friends) might be more willing to help their mates than complete strangers in fetching the desired content within the P2P overlay. Hence, an approach is devised to guarantee that P2P users belonging to an OSN are guaranteed a better service when critical conditions build up, i.e., when bandwidth availability is scarce. Different help strategies are proposed, and their improvements are numerically assessed, showing that the help of direct friends, two-hops away friends and, in the limit, of the entire OSN community brings in considerable advantages. The obtained results demonstrate that the amount of delivered video increases and the delay notably decreases, for those privileged peers that leverage their OSN membership within the P2P overlay.


Author(s):  
Roby Muhamad

Social network concerns the study of the structure of the patterns of relations among social entities. The study of social networks has a long history starting around 1930s when psychologist Moreno conducted the first known sociometric survey. Since then, the field of social network, first developed in sociology, has grown both empirically and theoretically, especially toward the end of the last century. The advent of powerful computing power and the Internet spurred growth on social network research. This combination of the proliferation of digital traces and increases in computing power provides opportunities to study large scale social networks and relevant dynamics.


MIS Quarterly ◽  
2021 ◽  
Vol 45 (2) ◽  
pp. 925-966
Author(s):  
Zhepeng (Lionel) Li ◽  
Yong Ge ◽  
Xue Bai

In social networks, social foci are physical or virtual entities around which social individuals organize joint activities, for example, places and products (physical form) or opinions and services (virtual form). Forecasting which social foci will diffuse to more social individuals is important for managerial functions such as marketing and public management operations. In terms of diffusive social adoptions, prior studies on user adoptive behavior in social networks have focused on single-item adoption in homogeneous networks. We advance this body of research by modeling scenarios with multi-item adoption and learning the relative propagation of social foci in concurrent social diffusions for online social networking platforms. In particular, we distinguish two types of social nodes in our two-mode social network model: social foci and social actors. Based on social network theories, we identify and operationalize factors that drive social adoption within the two-mode social network. We also capture the interdependencies between social actors and social foci using a bilateral recursive process—specifically, a mutual reinforcement process that converges to an analytical form. Thus, we develop a gradient learning method based on a mutual reinforcement process that targets the optimal parameter configuration for pairwise ranking of social diffusions. Further, we demonstrate analytical properties of the proposed method such as guaranteed convergence and the convergence rate. In the evaluation, we benchmark the proposed method against prevalent methods, and we demonstrate its superior performance using three real-world data sets that cover the adoption of both physical and virtual entities in online social networking platforms.


2014 ◽  
Vol 530-531 ◽  
pp. 701-704 ◽  
Author(s):  
Xiang Min Ren ◽  
Bo Xuan Jia ◽  
Ke Chao Wang ◽  
Jian Cheng

Social network is a collection of interrelated social actors, including individuals, groups, organizations, enterprises, even countries, is playing more and more important role in our life. But there are a lot of individual information in social network, it would violate individual privacy when publishing and analyzing the information. To avoid privacy disclosure and prevent privacy attacks, some k-anonymity privacy protection methods of social network are presented. In this paper, we represent the models of anonymization in social network and its key points, including definition, attack, and usefulness. We compared the difference among the proposed anonymization methods and techniques of privacy preserving in social networks. Finally, potential challenges in social network are proposed.


2013 ◽  
Vol 4 (4) ◽  
pp. 94-100
Author(s):  
D Veerasamy

Social networks have become a way of life for many people who use them to connect and communicate with the world at large. Social media is defined as any tool or service that uses the Internet to facilitate conversations. Facebook is one of the most popular social networking sites (SNSs) and has a total of 55 million active users worldwide with an average of 250000 new registrations per day. After Yahoo, MySpace and Google, Facebook is also the fourth most popular SNS in South Africa. The purpose of the paper was to determine whether social networks have an influence on higher education students’ lifestyles and behaviour. This research was descriptive and quantitative in nature. The sample comprised 386 students studying at the Durban University of Technology (DUT). The results indicated that the majority of the respondents preferred Facebook as their social network of choice. More than half of the respondents indicated that they access their preferred social network five times or more per day. The majority of the respondents agreed that social networks allow for global interaction and that maintaining relationships has become easier with social networking,


Management ◽  
2019 ◽  
Author(s):  
Sana Ansari ◽  
Dalhia Mani

The field of social networks focuses on the relationships among social actors, and on patterns that emerge from the structure of the social network and its implications (Wasserman and Faust’s Social Network Analysis: Methods and Applications). Social network research argues that actors (e.g., individuals or firms) are embedded within a network of relations, and that their behavior and choices cannot be studied independent of the social relations that shape and structure behavior. Social network perspective views relations among the social actors as ties and regular patterns in relationship as structure. Ties are the relational linkages that allow flow of resources between the actors, both tangible and intangible. Multiple actors form a web of relational ties, which can be either economic, social, or political. Networks can be of different types based on the content of the relational tie between the actors. For instance, collaboration ties between actors make a collaboration network or a co-author relation between actors makes a co-authorship network. Networks can also be at different levels of analysis—for instance, an intraorganizational friendship network is at the level of individuals while a network of intercountry trade relations is at the level of country. Ties between actors can be of different strengths (for instance, friends who meet daily versus once a year) and can also be negative or positive ties (e.g., competition networks versus collaboration networks). This article summarizes the latest research on social ties and network structure by focusing on the main thematic discussions in the field: (1) networks and strategic, governance behavior; (2) workplace networks; (3) collaboration and knowledge networks; (4) networks, personality, and individual differences; (5) entrepreneurial and family business networks; and (6) networks and social media. To ensure a comprehensive review of the topic, the article used search keywords, “networks,” or “network structure,” or “social networks,” or “social ties,” and was limited to articles in the top fourteen management journals, namely: Academy of Management Journal, Strategic Management Journal, Organization Science, Management Science, American Journal of Sociology, American Sociological Review, Administrative Science Quarterly, Academy of Management Review, Journal of Management Studies, Journal of Business Venturing, and Entrepreneurship Theory and Practice. The search was further limited to the six-year period from 2014–2019, since previous articles on organizational networks and brokerage in Oxford Bibliographies have summarized the research in this domain prior to 2014.


Sign in / Sign up

Export Citation Format

Share Document