社会化网络服务（SNS）用户信息分享行为研究

社会化网络服务已成为重要的信息分享渠道,用户不仅是信息的使用者,而且也是信息的提供者。在社会化网络服务平台上,用户之间的信息分享会促进平台的发展,信息分享行为是社会化网络服务平台上重要的用户行为之一。本文主要从用户视角和信息传播视角入手,分别从社会资本理论、信息传播模式等方面分析有关社会化网络服务用户信息分享行为的研究。最后,指出理论研究尚未完善的地方以及进一步研究的方向。     

LBS技术在移动设备中的发展与研究

目前流行的LBS整合了互联网平台和移动数据平台,创建了基于地理位置的信息服务,整合了线上线下资源,实现了全方位的社会化网络服务系统,LBS的发展趋势将会成为LBS+SNS+商业+娱乐的整合。     

基于WebGIS的地理社交网络空间构建

现代社会电子社交的网络越大越大,基于WebGIS的地理社交网络服务也融入了人们的生活.地理社交网络推出了很多位置信息服务,受到平台框架与语言编写的限制,定位精度受到了很大的影响,而地理位置服务也大多停留于签到与信息分享层面上,并未真正实现空间位置服务.本文对我国网络地理信息系统结构和实现的技术进行研究,提出了基于WebGIS的地理社交网络构建,为人们的出行服务更顺畅服务,满足无网络离线状态的地图查询与应用.     

安徽气象为农服务大数据平台设计与应用

从安徽省气象为农信息服务的个性化、精准化、智能化需求出发,采用Hadoop架构、自然语言处理、相关度分析、大数据可视化等大数据和人工智能相关技术,研发安徽省气象为农服务大数据平台。汇集安徽省多部门涉农数据资源,通过建立用户行为画像、网络服务热点的预测,开展精准化的服务产品相关性推荐服务,并跟踪评估信息服务产品的网络传播服务效果,指导后续关键农时农事建议和决策服务产品的研发与制作,同时建立气象为农服务大数据展示系统,探索实现气象为农信息服务从“人找信息”到“信息找人”的转变。该平台已在安徽气象为农业务服务中应用,提升了服务能力,具有较好的行业知名度和社会影响力。     

社交网络服务中的多维空间视频推荐算法

视频推荐作为一项帮助用户迅速找到其最感兴趣视频的关键技术,是社交网络服务中比较重要的研究内容之一。传统推荐算法未能充分利用视频社会化网站中的多维信息,会导致冷启动和数据稀疏的问题。为此,提出一种社交网络服务中的多维空间视频推荐算法。综合分析构成视频社会化网络的多维信息源要素,在此基础上,通过构建多维聚类空间,进而实现基于多维聚类空间的视频推荐算法,利用构成视频社会化网络的多维信息源要素,为视频的个性化推荐提供信息来源,以解决冷启动和数据稀疏问题。实验结果表明,该算法在视频推荐准确度方面相对于传统视频推荐算法有明显提高。     

社会网络分析技术在科研信息化中的应用

e-Science 和 Web2.0 的发展,促进了科研信息的开放和共享。科研人员对信息的依赖程度日渐加深,对知识服务、社会化信息的感知提出了更高的要求。科研人员在科研活动中形成了一张无形的社会网络,即学术社会网络。应用社会网络分析技术研究学术社会网络,一方面可以从宏观上通过对网络结构进行分析,了解当前的科研合作状况,提供科研管理的科学支持,另一方面可从微观的个人影响力、关系预测等多个侧面进行分析,深化信息服务。本文将重点介绍社会网络分析技术在当前科研信息化的应用实例,包括针对学术社会网络开展的实证研究工作,基于学术社会网络的合作者推荐技术,以及面向科研用户的支持知识共享和学术交流的学术社交平台。     

理解社会网络化-《Facebook效应》序

读这本《Facebook效应》,我第一次产生重新推敲SNS(Social Networking Services)译法的感觉.现在把SNS译成什么样的都有,如社会化网络服务、社会性网络服务,社交网络服务等,我认为准确的译法也许应是社会网络化服务.     

社交网络服务系统核心功能的设计与实现

现如今,社交网站早已经走进了大家的生活,使用社交网络服务的人数与日俱增,不论是在信息传播还是在社会影响力方面,社交网络服务都对传统方式产生的很大的冲击。因此,本文介绍了社交网络发展的历史、现状,并着重分析了社交网络的核心功能更和实现方法。同时,介绍了当今社交网络使用的主要技术,以及它们的使用方法。另外,作为一个已经产生近10多年的网络事物,伴随着各种新技术的出现,对社交网络进行变革的要求变得越来越迫切。基于位置的服务、即时网络服务是其中的两大趋势。通过结合定位引擎技术,本文中介绍的系统实现了基于位置的社交网络服务;通过与手机客户端的整合,用户通过手机登陆社交网络的同时也实现了即时网络服务,在本文的最后对下一代社交网络的发展做出了展望。文章是对此次毕业设计的总结,其中详细介绍了社交网络服务系统核心功能的调研、设计与实现,还有定位服务端与Android手机客户端的通讯和整合。并通过展示服务器功能模块的核心代码的方式,展现了整个系统良好的结构和具体实现操作方法。     

基于超图嵌入和有限注意力的社会化推荐

近年来,社会化推荐作为推荐算法之一被广泛应用于各大平台.由于引入了用户的社交信息,社会化推荐可以较好地缓解数据稀疏问题.然而,大部分社会化推荐难以高效地从原始信息中提取用户的有效信息,导致引入社会信息的同时也会引入大量噪声.为了解决上述问题,本文提出了SRBHL(Social Recommendation Based on Hypergraph embedding and Limited attention)模型,通过超图嵌入模块提取用户的历史行为信息和社交信息,以缓解原始目标用户数据稀疏问题,并结合有限注意力模块来过滤原始信息的噪声,最后将得到的有效好友信息用于推荐.在Yelp-Urbana、Yelp-Phoenix和Epinions3个真实数据集上的实验结果表明SRBHL模型相比其他的推荐算法表现更出色.此外,本文还对SRBHL模型进行了鲁棒性分析,并给出了模型最优参数的取值范围.     

基于人工智能推荐算法的智能家庭社会服务机制

随着社交网络时代的来临,社交网络的类型逐渐覆盖到不同的用户群体,对不同用户群体进行社交网络需求的潜力挖掘是目前的研究热点。本文研究基于人工智能推荐算法构建家庭社交网络的多级圈层结构,并以此提出家庭和亲属的智能推荐算法,以智能算法和家庭这一特殊群体的社交模式设计由个人信息模块、基本功能模块、家庭信息模块、应用服务模块和开放API模块所构成的家庭社交网络系统。研究结果表明,在数据量达到一万以上时,智能推荐算法的执行效率是非智能推荐算法的3倍左右,集群节点数对执行效率有显著影响。此外,智能推荐算法下的社交系统表现出良好的使用效果,这说明智能推荐算法具有较高的实用性。通过对家庭社会服务进行数据化的推荐算法研究,以及对算法执行效率进行定量验证,为社交网络服务机制提供了数据支持,验证了家庭社会服务的市场潜力。     

Exploring the dual outcomes of mobile social networking service enjoyment: The roles of social self-efficacy and habit

Enjoyment experience has been generally regarded as a positive element which can drive various aspects of system usage. Little research has examined its potential adverse outcomes, especially in an emerging mobile services context. This study investigates the dual effects of enjoyment on mobile social networking service (Mobile SNS) usage behaviors by focusing on not only its positive outcomes but also its potential adverse consequences. In addition, this study explores the impacts of social self-efficacy and habit on these dual causal processes. A research model is developed and empirically tested using data collected from 398 mobile SNS users in China. The structural equation modeling analysis results indicate that enjoyment significantly affects both mobile SNS high engagement and mobile SNS addiction behaviors. Mobile SNS habit mediates the associations between mobile SNS enjoyment and mobile SNS addiction behaviors. Social self-efficacy directly affects mobile SNS users' enjoyment experience, and it also has important indirect impacts on the dual processes by effectively enhancing mobile SNS users' high engagement and alleviating their addiction behaviors. The theoretical and practical implications of our findings are also discussed.     

Understanding How People Select Social Networking Services: Media Trait,Social Influences and Situational Factors

Social networking services (SNSs) have become very popular, and many Internet users use two or more SNSs. However, little research has been done to understand how and when users select multiple SNSs in series. This study investigates Internet users’ SNS selection behavior in daily life. We adopt the notion of media repertoire to explore how Internet users select SNSs in combination, and we adopt uses and gratifications theory to identify the values that drive these users to choose specific SNSs. We interviewed 40 Taiwanese people to explore the media traits, situational factors and social influences that affect users’ SNS selection behavior. The findings of this study can help SNS companies to improve SNS functions, and help marketers devise marketing strategies for target audiences and find suitable SNS platforms on which to communicate with consumers.     

Should I stay or should I go? The moderating effect of self-image congruity and trust on social networking continued use

Recent reports show that although users of large online social networks (such as Facebook) score low in terms of satisfaction, they manage to retain, or even increase, their user base. This study sheds an exploratory light on the reuse behaviour of online social network services (SNS). Specifically, we investigate the moderating effects of self-image congruity and trust on the relationship between satisfaction and continuance to use online SNS. To capture post-adoption behaviour of SNS users, we employ the expectation–confirmation model as a core structure for our theoretical model. The model is empirically tested using survey data collected from 288 Facebook users. Results reveal a possible trend suggesting that users perceiving a high match of the SNS with their self-image will be more loyal even if they experience low satisfaction levels. The same trend has been extracted for trust and its moderating effect on the relationship between satisfaction and usage continuance intention. This paper concludes with a discussion on the theoretical and practical implications of our findings.     

Branding with social media: User gratifications,usage patterns,and brand message content strategies

The emergence of social media provides a new platform for developing brand–consumer relationships. The aim of the current study is to examine the differences in Chinese users’ gratifications of different social media and the impact of brand content strategies on the quality of brand–consumer communication via social media. In the first study, 209 SNS and 161 microblog users were surveyed. Five dimensions of social media gratifications emerged from the factor analysis. Significant differences in the strengths of gratifications were found between SNS and microblog users. Usage patterns of SNS and microblog are analyzed and compared. In the second study, we examined the impact of users’ gratification and the type of social media on the effectiveness of different brand content strategies through a two-week experiment involving 60 SNS users and 61 microblog users. Implications for developing branding strategies on different social media platforms are discussed.     

Ambient Awareness to Strengthen the Family Social Network of Older Adults

Social networking sites (SNSs) provide ambient awareness of the interests and activities of friends and relatives helping them sustain and strengthen their social ties. Older adults who are not adopting SNSs might however feel like outsiders within their own families who increasingly rely on these services to socialize. Previous research has shown that situated displays can provide appropriate interfaces for older adults to use digital services. In this paper we explore how situated displays can intuitively provide ambient awareness to strengthen the family social network of older adults. We designed and developed Tlatoque, a situated display, to seamlessly integrate older adults into the SNS used by their relatives. The results of a 21-week deployment study of an initial version of Tlatoque in one extended family showed that the older adult became more conscious of relatives’ activities, which also enriched in-person encounters. However, relatives expected the older adult to reply to their posts in the SNS and Tlatoque lacked mechanisms for the older adult to provide feedback. We re-designed Tlatoque to incorporate means for enabling the older adult to share information back to the SNS. We conducted a second 21-week deployment study with another extended family to evaluate the use of this new version of the system. Our results indicate that the second design was successful in providing ambient awareness to the older adult as well as to her relatives. We conclude that situated displays that provide SNS services can assist the integration of older adults to their social network and contribute to enhance asymmetric relations between the older adult and younger relatives.     

Continuance usage of corporate SNS pages: A communicative ecology perspective

This study develops a research model that explains the continuance of corporate social network service (SNS) pages. In order to find antecedents that influence end users’ continuance intention, this study adopts communicative ecology theory from media and communication studies. Results indicate that the quality of social interaction is the most salient feature, as indicated by the fact that it has the highest impact on perceived usefulness and enjoyment. Moreover, content quality also increases both perceived usefulness and enjoyment, while SNS platform quality and service quality increase perceived usefulness only. In addition, perceived network size moderates the impact of social interaction quality on perceived enjoyment.     

Crowdsourcing social network service for social enterprise innovation

Social enterprises (SE) have developed various innovative business models to accomplish both social and business values for years. Not few SE’s persons have observed some critical and urgent social issues as well as human problems, but just few SE’s social media or crowdsourcing services can be provided people an efficient way to interact for these social problems. Thus, the research is to solve the need which is an integrative platform of social media and crowdsourcing service to support business innovation of social enterprise. Such a SE-specific crowdsourcing social network service (SNS) facilitate people can obtain the shared resources to further achieve the projects (i.e, volunteer activities) or even start up an innovative SE (i.e., lumni, 20%+, The Big Issue). In order to achieve SE’s charitable objective, this research is to propose and design an integration of social network and crowdsourcing service – HIVE that can provide people to post ideas, share resources, or even attend the crowdsourcing projects by the different resources. Thus, HIVE can give users to seek business opportunities, collect, connect, and users’ data analysis for social and human resources. HIVE even can provide several ways to facilitate human and resource corporations to support SE’s business innovation based on six pre-defined areas of SE and deal with the critical matching process.     

Comparative effect of company-driven SNS activity vs. consumer-driven SNS activity on firm value: Evidence from facebook

As mobile technology and social media have advanced, companies have become more and more motivated to make use of social network services (SNS) such as Facebook to increase future firm performance. Perusing the literature on the association between SNS and firm performance, we found very few empirical studies of the comparative effect of company-driven activity (e.g. posting) and consumer-driven activity (e.g. liking, commenting, sharing) on firm performance. Moreover, specific SNS activities affecting firm performance in the present, future, or both have not been explicitly identified. Hence, we developed an empirical model to identify and find differences between the effects of SNS activities on firm performance in the present (as measured by returns on investment) or future (as measured by Tobin’s q) to improve our understanding of the impact of corporate SNS as a marketing channel. Text mining techniques are applied in this study to identify SNS activities from SNS data. The results suggest that SNS contributes significantly to future firm performance, as evidenced by increases in Tobin’s q. Moreover, company-driven activities affect future value, while consumer-driven activities affect present value. Implications from these results are discussed.     

Personalized recommender system based on friendship strength in social network services

The rapid growth of social network services has produced a considerable amount of data, called big social data. Big social data are helpful for improving personalized recommender systems because these enormous data have various characteristics. Therefore, many personalized recommender systems based on big social data have been proposed, in particular models that use people relationship information. However, most existing studies have provided recommendations on special purpose and single-domain SNS that have a set of users with similar tastes, such as MovieLens and Last.fm; nonetheless, they have considered closeness relation. In this paper, we introduce an appropriate measure to calculate the closeness between users in a social circle, namely, the friendship strength. Further, we propose a friendship strength-based personalized recommender system that recommends topics or interests users might have in order to analyze big social data, using Twitter in particular. The proposed measure provides precise recommendations in multi-domain environments that have various topics. We evaluated the proposed system using one month's Twitter data based on various evaluation metrics. Our experimental results show that our personalized recommender system outperforms the baseline systems, and friendship strength is of great importance in personalized recommendation.     

社交网络用户标签预测研究

随着社交网站的流行以及用户的大规模增加,社交网络用户行为分析已经成为社交网站进行网站维护、性能优化和系统升级的重要基础,也是网络知识挖掘和信息检索的重要研究领域。为了更好地理解社交网络用户添加个人标签的行为特征,该文基于大约263万个微博用户的真实数据,对用户标签的分布进行了研究和分析。我们主要考察了用户标签的宏观分布特征,以及用户标签与关注对象的标签分布之间的联系,发现微博用户给自己添加标签时,在开始阶段倾向于使用反映个性的标签,之后会出于从众心理而选用大众化标签。我们将研究发现运用到基于关注关系的标签预测算法中,结果证实相关分析对于社交网站的标签推荐等课题具有一定的参考意义。