从社会符号学视角解读上海世博会吉祥物

当今社会已经步入了一个数字化和信息化的时代,随着人们的交流方式逐渐由文字向图像化转变,话语分析的研究范围也随之延伸到语言文字之外的图片、声音、颜色等社会符号。文章运用社会符号学框架下的视觉语法理论分析了2010年上海世博会吉祥物-海宝这个多模态语篇,说明除语言文字以外的其他社会符号也是意义的源泉。     

整合营销传播理论与新广告主义革命

整合营销传播（IMC）理论在广告业界的导入并未完成中国广告传播理念的根本性转移。中国广告尚期待一场深层意义上的实践性变革,即实现从集＂销售主义＂大成的＂整合营销传播（IMC）＂到＂人文关怀与社会关怀＂相融汇的新广告范式建构,亦即本文所论及的＂新广告主义革命＂,以此完成广告传播的观念重建,最终实现从以物为本到以人为本的根本性变革。     

高职高专专门用途英语(ESP)教学研究

本文通过对ESP的概念、特征以及与EGP的关系的分析,明确ESP在高职高专大学英语教学中的定位,旨在推动高职高专以ESP教学为重点的英语教学改革。     

资源生产供应链履行社会责任的内在动力研究

运用博弈论的基本思想,通过构造一个资源生产供应链,从资源保护这个角度出发,以资源生产供应链中的节点企业——资源开采商开采自然资源为例,对资源生产供应链履行社会责任的内在动力进行了研究。结果表明：对资源开采商合作开采带来的收益增量进行合理分配,既能使资源开采商进行合作,又能实现供应链系统与各资源开采商的帕累托最优。     

我国失地农民社会保障制度问题

近年来,随着我国城镇化、工业化进程加快,大量农村集体土地被征用,由此带来的是失地农民的数量不断增加。土地对农民而言,具有生产资料和社会保障双重功能,农民一旦失去土地立即成为种田无地、就业无岗、社保无份的"三无"人群,生活陷入困境,成为一个新的弱势群体。因此,如何保护失地农民的合法权益,解决失地农民社会保障的后顾之忧,就成为当前迫切需要解决的一个经济问题和关乎社会稳定和改革发展大局的社会问题。     

利用信任和社会网络的资源发现方法

为解决无结构对等网络中因恶意节点的欺诈行为造成的搜索不可靠问题,提出了利用信任和
社会网络(TSN)的资源发现方法;提出转发信任度、路由信任度和交易信任度的概念,用来
反映节点提供可靠服务的能力. 在节点选择朋友进行消息转发时,优先选择综合信任度高且
相关度高的朋友节点转发查询消息. 实验结果表明,TSN方法在资源搜索阶段有效屏蔽了恶
意节点,保证了请求节点获得服务资源的可靠性,提高了搜索效率.     

PAIDD: a hybrid P2P-based architecture for improving data distribution in social networks

Rapid growth in social networks(SNs)presents a unique scalability challenge for SN operators because of the massive amounts of data distribution among large number of concurrent online users.A request from any user may trigger hundreds of server activities to generate a customized page and which has already become a huge burden.Based on the theoretical model and analytical study considering realistic network scenarios,this article proposes a hybrid P2P-based architecture called PAIDD.PAIDD fulfills effective data distribution primarily through P2P connectivity and social graph among users but with the help of central servers.To increase system efficiency,PAIDD performs optimized content prefetching based on social interactions among users.PAIDD chooses interaction as the criteria because user’s interaction graph is measured to be much smaller than the social graph.Our experiments confirm that PAIDD ensures satisfactory user experience without incurring extensive overhead on clients’network.More importantly,PAIDD can effectively achieve one order of magnitude of load reduction at central servers.     

A social interaction system based on cloud computing for mobile video telephony

As the use of smartphones become popular,people heavily depend on smartphone applications to deal with their social activities.For this reason,traditional message texting between mobile applications does not fulfill the versatile requirements of social networking.Many mobile applications use multimodality to deliver multimedia messages including sticker,voice and photo message,video call,and snap movie to enhance the communicative capability.However,without face-to-face interaction,people may fail to detect the other side’s non-verbal social behavior such as fine-grain facial expressions,body movements,or hand gesture.During social interaction,non-verbal behavior conveys information about the involved individuals and help the speakers express their social emotion in an implicit way.It is so important for real-world face-to-face interaction but is often blocked on the mobile telephony.To cope with this problem,we propose an afective computing model to assist the representation of social emotion and then help the progress of social interaction on the mobile telephony.In this model,for the purpose of real-time afective analysis,we delegate the computing loading to the cloud side service and enhance the system’s scalability and availability.The result of this experiment approves the feasibility of our system design for the applications of social intelligent.Also,the system provides a research framework of the social intelligent system on the mobile telephony.     

Temporal evolution of contacts and communities in networks of face-to-face human interactions

Temporal dynamics of social interaction networks as well as the analysis of communities are key aspects to gain a better understanding of the involved processes, important influence factors, their effects, and their structural implications. In this article, we analyze temporal dynamics of contacts and the evolution of communities in networks of face-to-face proximity. As our application context, we consider four scientific coil- ferences. On a structural level, we focus on static and dynamic properties of the contact graphs. Also, we analyze the resulting community structure using state-of-the-art automatic community detection algorithms. Specifically, we analyze tile evolution of contacts and communities over time to consider the stability of the respective conmmnities. Furthermore, we assess different factors which have an influence on the quality of com- munity prediction. Overall, we provide first important insights into the evolution of contacts and communities in face-to-face contact networks.     

基于图卷积网络的微博新闻故事线抽取方法

微博作为人们获取和传播新闻事件的主要平台,隐藏着丰富的事件信息。从微博数据中抽取故事线能为用户提供一种直观的方式来准确理解事件演化,然而微博数据稀疏和上下文缺乏的特点为故事线抽取带来了挑战。因此,通过两个连续的任务从微博数据中自动抽取故事线：1）基于微博传播影响力对事件进行建模,并提取出首要事件;2）基于事件特征建立异构事件图,提出事件图卷积网络（E-GCN）模型来提升对事件间隐式关系的学习能力,从而实现事件的故事分支预测并链接事件。在真实数据集上从故事分支和故事线两个角度进行评测,结果表明所提方法在故事分支生成测评中,相较于贝叶斯模型、斯坦纳树和故事森林在F1值上,在Dataset1上分别高出28个百分点、20个百分点和27个百分点,在Dataset2上分别高出19个百分点、12个百分点和22个百分点;而在故事线抽取评测中,相较于故事时间线、斯坦纳树和故事森林在正确的边准确率上,在Dataset1上分别高出33个百分点、23个百分点和17个百分点,在Dataset2上分别高出12个百分点、3个百分点和9个百分点。