News Update on Social Relationship Research: May – 2019

The social relationship driving power of Internet of Things

Social web of Things (SIoT) integrates the social network with the web of Things (IoT) and has become a hot analysis issue for its potential to support novel IoT applications and networking services in additional effective and economical ways in which. The computer programme, that is primarily designed for social network users to accumulate interested info, conjointly plays a vital role in SIoT. There even exist search engines specially designed for SIoT. employing a computer programme, individuals will simply notice the good devices in SIoT. Specifically, a groundwork engine assists the knowledge dissemination, i.e., sanctioning users (both humans and things) to access interested objects (both humans and things) with keywords-searching and transferring contents from the supply on to potential interested users. attendant such processes, the SIoT evolves as new links emerge between users and their interested objects. during this paper, we tend to aim to quantitatively characterize however a groundwork engine influences the social relationship within the IoT. Firstly, we tend to imply that the computer programme is the medium between the social network and also the IoT, and so we tend to propose a groundwork Social web of Things (SSIoT) model for SIoT evolution. Secondly, we tend to adopt six performance metrics, namely, degree distribution, networkdiameter, average distance, network density, network stability, and user betweenness. in theory, we tend to prove that the degree distribution follows AN intense power-law, the network diameter and also the average distance shrink, network density, network stability, and user betweenness ar larger in SSIoTs. Thirdly, we tend to quantitatively show that a groundwork engine accelerates malicious code propagation in SIoTs. Finally, supported four real-world knowledge sets (i.e., CDBLP, Facebook, Weibo, and P2P), we tend to verify our theoretical findings. [1]

A social recommendation method based on the integration of social relationship and product popularity

Web 2.0 technology fosters the flourishing growth and development of social networks. additional and additional folks area unit taking part within the activities on social networks to act and share info with one another. Thus, customers area unit usually creating their buying selections supported info from the net like reviews, ratings, and comments on product, particularly from their trusty friends. However, a good quantity of accessible info might cause the matter of knowledge overload for customers. In seeking to achieve a decent recommendation performance by taking the high-voltage factors into consideration as way as doable, this paper proposes a unique social recommendation technique on the premise of the mixing of interactions, trust relationships and products quality to predict user preferences, and advocate relevant product in social networks. additionally, the projected technique in the main focuses on analyzing user interactions to infer their latent interactions in accordance with the user ratings and corresponding reviews. in addition, users could also be tormented by the recognition of product, thus this issue has conjointly been taken into thought during this work. The experimental results show that the projected advocateation technique incorporates a higher recommendation performance in comparisons to alternative ways as a result of the projected technique will accurately analyze user preferences and additional recommend high-voltage product to focus on users in social networks to support their purchase deciding. moreover, the projected technique can’t solely scale back the time and energy users pay on querying info, however conjointly absolutely relieve the matter of knowledge overload. [2]

The heterogeneous relationship between board social ties and corporate environmental responsibility in an emerging economy

Firms in emerging economies are faced with multiple, incompatible institutional forces in their environmental activities. Which of these forces will be dominant and instantiated within an organization is partly determined by the social relationships that a firm maintains with external actors. This paper investigates the relationship between board social ties and the level of environmental responsibility undertaken by firms in China, an emerging economy, by categorizing board social ties into three types in terms of the three isomorphic forces in the institutional field (coercive, normative and mimetic). Drawing on institutional and agency theories, using a sample of listed firms in environmentally sensitive industries, and a generalized least squares regression method, the results provide empirical evidence that ties that are linked to coercive and normative forces (i.e., political organizations and universities) are related to a higher level of environmental responsibility; however, those that are linked to mimetic forces (i.e., industrial peers) have a negative association with environmental responsibility, which is mitigated by CEO power. These findings suggest that the heterogeneous effects of board social ties on environmental responsibilities experienced by firms in a context of environmentalism are at an early stage. [3]

Costs and benefits of social relationships in the collective motion of bird flocks

Current understanding of collective behaviour in nature is predicated for the most part on models that assume that identical agents adapt identical interaction rules, however essentially interactions could also be influenced by social relationships among cluster members. Here, we tend to show that social relationships rework native interactions and collective dynamics. we tend to half-tracked individuals’ three-dimensional trajectories at intervals flocks of jackdaws, a species that forms long pair-bonds. reflective this system, we discover that flocks contain internal sub-structure, with separate pairs of people tied along by spring-like effective forces. at intervals flocks, paired birds interacted with fewer neighbours than mismatched birds and flapped their wings additional slowly, which can end in energy savings. However, flocks with additional paired birds had shorter correlation lengths, that is probably going to inhibit economical data transfer through the flock. Similar changes to cluster properties emerge naturally from a generic self-propelled particle model. These results reveal a vital tension between individual- and group-level edges throughout collective behaviour in species with differentiated social relationships, and have major biological process and psychological feature implications. [4]

Effect of Symbiotic Relationship on Self-organized Startup Entrepreneurship, an Innovative Synergy

Self-organized theory-series square measure up perpetually with sturdy rationalization base for entrepreneurship, with dependent theory because the most vital one in all that plays terribly crucial role for startups ‘symbiotic relationship survival rate, goodwill and growth potential on self-organized startup entrepreneurship. The study used structural equation model in analyzing the sampled information of 399 responses, showing that each one the measuring models and constructs used match the information well therefore Absolute match  index, progressive match index and penurious match index were all at intervals the appropriate ranges. The 3 constructs, dependent relationship, innovative concepts and social relationship, square measure indicative that they need the flexibility to influence self-organized startup businesses. The results of the take a look at on the 2 hypothesis square measure confirmed and supported. A unit amendment in dependent relationship will cause zero.192 increase in tiny business startups while a share amendment in innovative concepts will absolutely influence tiny startups by zero.274%.[5]

Reference

[1] Fu, C., Peng, C., Liu, X.Y., Yang, L.T., Yang, J. and Han, L., 2019. Search engine: The social relationship driving power of Internet of Things. Future Generation Computer Systems92, pp.972-986. (Web Link)

[2] Lai, C.H., Lee, S.J. and Huang, H.L., 2019. A social recommendation method based on the integration of social relationship and product popularity. International Journal of Human-Computer Studies121, pp.42-57. (Web Link)

[3] Zou, H., Xie, X., Qi, G. and Yang, M., 2019. The heterogeneous relationship between board social ties and corporate environmental responsibility in an emerging economy. Business Strategy and the Environment28(1), pp.40-52. (Web Link)

[4] Costs and benefits of social relationships in the collective motion of bird flocks

Hangjian LingGuillam E. Mclvor,Kasper van der Vaart,Richard T. Vaughan,Alex Thornton &Nicholas T. Ouellette

Nature Ecology & Evolution 3, 943–948 (2019) (Web Link)

[5] Dodor, A., Li, C., Gumah Akolgo, I. and Quacoe, D. (2018) “Effect of Symbiotic Relationship on Self-organized Startup Entrepreneurship, an Innovative Synergy”, Journal of Economics, Management and Trade, 21(4), pp. 1-13. doi: 10.9734/JEMT/2018/40719. (Web Link)

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