Research on the Continuous Participation of Virtual Brand Community in Decision-Making Based on Social Influence Theory

Based on the social influence theory,the influence of virtual brand community members’perceived value on social influencing factors is discussed,and the influence of social influencing factors on virtual brand community members’continuous participation in decision-making is analyzed.Through an empirical analysis of the survey data of Xiaomi users in the Xiaomi Community,the results showed that the perceived value of virtual brand community members significantly and positively affects social influencing factors,which also significantly and positively affect the members’continuous participation in virtual brand communities.Therefore,only by sharing valuable information resources and improving the efficiency of information flow,thereby enhancing the perceived value of the community and increasing the stickiness of members to the virtual community,will we have an opportunity to enhance the interaction among members and effectively promote continuous participation in community activities through the strong bonds formed among members.

UGC-Driven Social Influence Study in Online Micro- Blogging Sites

In Web 2.0 era,the content on a web page is increasingly generated by end users,rather than limited number of administrators.Hence,large number of User Generated Content(UGC) has driven the explosion of content in the web.Thanks to UGC,the pattern of web usage has evolved from download dominated way to a hybrid one with both information download and upload.Large number of UGC has unveiled great capacity of information that is unavailable for researchers before,such as individual preferences,social connections,and etc.In this paper,we propose a novel model which studies the UGC in micro-blogging web sites,the largest and fastest information diffusion media online,and evaluate the social influence for an arbitrary individual.Experimental results show that our model outperforms state-of-the-art techniques in social influence evaluation in both the running time and accuracy.

A Study on the Influence of Social Media Use on Psychological Anxiety among Young Women

To explore the relationship between social influence,social comparison,clarity of self-concept,and psychological anxiety among young women during their usage of social networking sites,our study selected 338 young women aged 14-34 from the social site platforms of Little Red Book and Weibo for questionnaire surveys.The Passive Social Network Utilization Scale,Social Comparison Scale(SCS),Social Influence Questionnaire,Self-Concept Clarity Scale(SCCS),and Generalized Anxiety Disorder Scale(GAD-7)were employed to measure the subjects.Our results show that the frequency of passive social media use is positively related to the level of psychological anxiety.Social comparison,social influence,and unclear self-concepts under social media use are negatively predictive of psychological anxiety.The chain mediation effects indicate that social comparison and social influence under social media use negatively predict the clarity of self-concept,thus having a negative impact on the psychological health of young women.Therefore,young women should strengthen their self-concepts,control their frequency of social media usage,avoid addiction,and pay special attention to their frequency of passive use,in order to protect their psychological health.Our study provides some practical implications and insights regarding the relationship between young women’s social media use and psychological health.

Social influence and spread dynamics in social networks

Social networks often serve as a critical medium for information dissemination, diffusion of epidemics, and spread of behavior, by shared activities or similarities be- tween individuals. Recently, we have witnessed an explosion of interest in studying social influence and spread dynamics in social networks. To date, relatively little material has been provided on a comprehensive review in this field. This brief survey addresses this issue. We present the current significant empirical studies on real social systems, including network construction methods, measures of network, and newly em- pirical results. We then provide a concise description of some related social models from both macro- and micro-level per- spectives. Due to the difficulties in combining real data and simulation data for verifying and validating real social sys- tems, we further emphasize the current research results of computational experiments. We hope this paper can provide researchers significant insights into better understanding the characteristics of personal influence and spread patterns in large-scale social systems.

Social Influence Study in Online Networks： A Three-Level Review

Social network analysis （SNA） views social relationships in terms of network theory consisting of nodes and ties. Nodes are the individual actors within the networks; ties are the relationships between the actors. In the sequel, we will use the term node and individual interehangeably. The relationship could be friendship, communication, trust, etc. These reason is that these relationships and ties are driven by social influence, which is the most important phenomenon that distinguishes social network front other networks. In this paper, we present an overview of the representative research work in social influence study. Those studies can be classified into three levels, namely individual, community, and network levels. Throughout the study, we are able to unveil a series of research directions in future and possible applications based on tile state-of-the-art study.

The Political and Social Influences of the West ‘Us’ in the Arab World ‘Others’

Western influence is the upshot of two centuries of Western dominance.Their position of power has undermined the prerogatives of many nations,which is evident in the West pushing certain political and cultural ideals.Their privileged and powerful political and cultural status and the superiority of their civilization led them to view the rest of the world as‘Others’,being politically,and culturally inferior.This is what made the West identify the policy and the economy in the world and impose the liberal democracy and the Western social and cultural patterns on‘others’,rendering them as parameters for civilization and political development.In this paper,we will focus on the influence of the West‘Us’on the Arab world‘Others’and the political and social effects it has had in the region.The current study is twofold.Firstly,we will look at the recent development of the Arab world in current events,which are largely driven by Western interference in the region.The second factor is the erosion of the Arab heritage amid the wide adoption of Western cultures,and its social and political impact.

Identification of Influential Users in Online Social Network: A Brief Overview

Information networks where users join a network, publish their own content, and create links to other users are called Online Social Networks (OSNs). Nowadays, OSNs have become one of the major platforms to promote both new and viral applications as well as disseminate information. Social network analysis is the study of these information networks that leads to uncovering patterns of interaction among the entities. In this regard, finding influential users in OSNs is very important as they play a key role in the success above phenomena. Various approaches exist to detect influential users in OSNs, starting from simply counting the immediate neighbors to more complex machine-learning and message-passing techniques. In this paper, we review the recent existing research works that focused on identifying influential users in OSNs.

Chinese Students’ Adaptation of Social Intercourse Influenced by Different Cultural Contexts of China and America in American Universities

1 Statement of the Purpose (1) Statement of the purpose The purpose of the research isto study Chinese studends' adaptation of social intercourse influenced by different cultural contexts of China and America in American universities.And the study will also try to find out the exact problems and obstacles during Chinese students' adapting period in American universities.

The Influence of the Changes in Social Trends of Thought in Japan

The social trend of thought is the trend of thought that is of extensive influence formed in a certain period of time in a given society. It o-riginates from the changes in international environment and domestic social situation, reflecting the interests and demands of a given group of people and producing a great influence on the foreign and domestic policies and the future trend of the society. One prominent feature of

Exploiting Geo-Social Correlations to Improve Pairwise Ranking for Point-of-Interest Recommendation

Recently, as location-based social network(LBSN) rapidly grow, point-of-interest(POI) recommendation has become an important way to help people locate interesting places. Nowadays, there have been deep studies conducted on the geographical and social influence in the point-of-interest recommendation model based on the rating prediction. The fact is, however, relying solely on the rating fails to reflect the user's preferences very accurately, because the users are most concerned with the list of ranked point-of-interests(POIs) on the actual output of recommender systems. In this paper, we propose a co-pairwise ranking model called Geo-Social Bayesian Personalized Ranking model(GSBPR), which is based on the pairwise ranking with the exploiting geo-social correlations by incorporating the method of ranking learning into the process of POI recommendation. In this model, we develop a novel BPR pairwise ranking assumption by injecting users' geo-social preference. Based on this assumption, the POI recommendation model is reformulated by a three-level joint pairwise ranking model. And the experimental results based on real datasets show that the proposed method in this paper enjoys better recommendation performance compared to other state-of-the-art POI recommendation models.

Remote Influence Tactics

Research into social influence theory has been extensive and has repeatedly shown the power that influence tactics exert over individuals in an organization. Despite the extant conceptualizations of political influence tactics in organizations, very little research has focused on how these tactics play out for organizations implementing more autonomous team settings, whose interactions are not proximally located close to one another. By extending social influence theory to the inclusion of media synchronicity theory, this research contributes insight into how political influence tactics may operate across a variety of media in organizations employing remote work structures. A conceptual model of remote influence tactics is developed and the implications are discussed as part of this research agenda.

Recommending Personalized POIs from Location Based Social Network

Location based social networks（ LBSNs） provide location specific data generated from smart phone into online social networks thus people can share their points of interest（ POIs）. POI collections are complex and can be influenced by various factors,such as user preferences,social relationships and geographical influence. Therefore,recommending new locations in LBSNs requires to take all these factors into consideration. However,one problem is how to determine optimal weights of influencing factors in an algorithm in which these factors are combined. The user similarity can be obtained from the user check-in data,or from the user friend information,or based on the different geographical influences on each user＇s check-in activities. In this paper,we propose an algorithm that calculates the user similarity based on check-in records and social relationships,using a proposed weighting function to adjust the weights of these two kinds of similarities based on the geographical distance between users. In addition,a non-parametric density estimation method is applied to predict the unique geographical influence on each user by getting the density probability plot of the distance between every pair of user＇s check-in locations. Experimental results,using foursquare datasets,have shown that comparisons between the proposed algorithm and the other five baseline recommendation algorithms in LBSNs demonstrate that our proposed algorithm is superior in accuracy and recall,furthermore solving the sparsity problem.

Empirical Analysis on Factors Affecting Mobile Internet Users’ Purchase Intention for 3G Handsets

The research on consumers' purchase intention for 3G handsets has important theoretical and practical value. This research puts forward four key factors which influence consumers' purchase intention based on the cue utilization theory, situational theory and social impact theory, then it establishes the study model for consumers' purchase intention of 3G handsets. Based on the result of the questionnaire survey and empirical analysis, the study shows that social influence is the most prominent factor in purchase intention. Moreover, as different from results of previous studies, the situational influence factors have no significant impact on purchase intention in the 3G handsets market. The results of the model provides a forceful evidence for operators' and handset manufacturers' decision-making of 3G handsets design and marketing strategies, and it will improve their social impact.

Intention to Use Mobile Augmented Reality in the Tourism Sector

This article examines the main variables that influence the intention to use Augmented Reality(AR)applications in the tourism sector in Jordan.The study model has been constructed based on the unified theory of acceptance and the use of technology2(UTAUT2),by incorporating a new construct(aesthetics)to explore the usage intention of Mobile Augmented Reality in Tourism(MART).A questionnaire was used and distributed to a sample of 450 participants.Data were analyzed using the Smart PLS version 3.0.for testing 12 hypotheses.29 measurement items were carefully reviewed based on previous studies that were selected to assess the research hypotheses.The findings revealed that the proposed model elucidates 35.7%of the variance in the users’intention to use MART.The results also showed that both performance expectancy and aesthetics were found to be the most significant factors at level(0.001).Four variables,respectively,were at level(0.01)which consisted of social influence,facilitating conditions,hedonic motivation,and price value.The weakest effect was effort expectancy at level(0.05).As the use of AR has become important for tourists,this study establishes a research base that can be built upon for future researchers.MART developers can benefit from the results of this research to design and deliver this service successfully and to ensure that its adoption by users is achieved.

ComRank： Joint Weight Technique for the Identification of Influential Communities

Recently, the community analysis has seen enormous research advancements in the field of social networks. A large amount of the current studies put forward different models and algorithms about most influential people. However, there is little work to shed light on how to rank communities while considering their levels that are determined by the quality of their published contents. In this paper, we propose solution for measuring the influence of communities and ranking them by considering joint weight composed of internal and external influence of communities. To address this issue, we design a novel algorithm called Com Rank: a modification of Page Rank, which considers the joint weight in order to identify impact of each community and ranking them. We use real-world data trace in citation network and perform extensive experiments to evaluate our proposed algorithm. The comparative results depict significant improvements by our algorithm in community ranking due to the inclusion of proposed weighting feature.

Psychometric properties of questionnaires to measure social ecological influences in Vietnamese children

Physical activity data in primary school-aged children are limited in Vietnam.Although tools to measure social ecological influences on physical activity are validated in English,they are not available in Vietnamese.Due to cultural and contextual differences,their psychometric properties need to be tested.Five scales were translated into Vietnamese and evaluated for internal consistency and test re-test reliability,including self-efficacy,perceived social influences,and beliefs self-administered by students,and parental support for physical activity and parental perceived safety of the neighbourhood,self-administered by parents.Compared to the original scales,two items from the parental perceived neighbourhood safety were removed due to the cultural context.Another item of the self-efficacy scale was also removed as it correlated poorly with the other items in the scale at both administrations.The adjusted scales were found to be reliable and appropriate for use among students and parents to measure social ecological influences on physical activity in the Vietnamese context.

An Efficient Two-Phase Model for Computing Influential Nodes in Social Networks Using Social Actions

The measurement of influence in social networks has received a lot of attention in the data mining community. Influence maximization refers to the process of finding influential users who make the most of information or product adoption. In real settings, the influence of a user in a social network can be modeled by the set of actions （e.g., ＂like＂, ＂share＂, ＂retweet＂, ＂comment＂） performed by other users of the network on his/her publications. To the best of our knowledge, all proposed models in the literature treat these actions equally. However, it is obvious that a ＂like＂ of a publication means less influence than a ＂share＂ of the same publication. This suggests that each action has its own level of influence （or importance）. In this paper, we propose a model （called Social Action-Based Influence Maximization Model, SAIM） for influence maximization in social networks. In SAIM, actions are not considered equally in measuring the ＂influence power＂ of an individual, and it is composed of two major steps. In the first step, we compute the influence power of each individual in the social network. This influence power is computed from user actions using PageRank. At the end of this step, we get a weighted social network in which each node is labeled by its influence power. In the second step of SAIM, we compute an optimal set of influential nodes using a new concept named ＂influence-BFS tree＂. Experiments conducted on large-scale real-world and synthetic social networks reveal the good performance of our model SAIM in computing, in acceptable time scales, a minimal set of influential nodes allowing the maximum spreading of information.

GREENCOMMUTE： AN INFLUENCE-AWARE PERSUASIVE RECOMMENDATION APPROACH FOR PUBLIC-FRIENDLY COMMUTE OPTIONS

Negative impacts produced by transportation sector have increased in parallel with the increase of urban mobility. In this paper, we introduce GreenCommute, a novel recommendation system which can facilitate commuters to take public fi＇iendly commute options, while provide support to alleviate the external cost in society, such as traffic pollution, congestion and accidents. In the meanwhile, a rewarding mechanism for persuading commuters is embedded in the proposed approach for balancing the conflict between personal needs and social aims. The allocation of reward values also takes users＇ influential degrees in the social network into consideration. Experimental results show that the GreenCommute can promote public friendly commute options more effectively in comparison to the traditional recommendation system.

Mathematical Models of Self-Appraisal in Social Networks

In social networks where individuals discuss opinions on a sequence of topics,the selfconfidence an individual exercises in relation to one topic,as measured by the weighting given to their own opinion as against the opinion of all others,can vary in the light of the self-appraisal by the individual of their contribution to the previous topic.This observation gives rise to a type of model termed a De Groot-Friedkin model.This paper reviews a number of results concerning this model.These include the asymptotic behavior of the self-confidence(as the number of topics goes to infinity),the possible emergence of an autocrat or small cohort of leaders,the effect of changes in the weighting given to opinions of others(in the light for example of their perceived expertise in relation to a particular topic under discussion),and the inclusion in the model of individual behavioral characteristics such as humility,arrogance,etc.Such behavioral characteristics create new opportunities for autocrats to emerge.

Discrete Opinion Dynamics on Online Social Networks

This paper focuses on the dynamics of binary opinions {＋1,-1} on online social networks consisting of heterogeneous actors. In our model, actors update their opinions under the interplay of social influence and self- affirmation, which leads to rich dynamical behaviors on online social networks. We find that the opinion leading to the consensus features an advantage of the initially weighted fraction based on actors＇ strength over the other, instead of the population. For the role of specific actors, the consensus converges towards the opinion that a small fraction of high-strength actors hold, and individual diversity of self-amrmation slows down the ordering process of consensus. These indicate that high-strength actors play an essential role in opinion formation with strong social influence as well as high persistence. Further investigations show that the initial fraction of high-strength actors to dominate the evolution depends on the heterogeneity of the strength distribution, and less high-strength actors are needed in the case of a smaller exponent of power-law distribution of actors＇ strength. Our study provides deep insights into the role of social influence and self-affirmation on opinion formation on online social networks.