《社交网络》:传记电影的虚构与拓写

《社交网络》是一部成功的传记电影。它提供了好莱坞影片人物传记拍摄的新型范式,相对以塑造人物而非讲述事件的方式打开人们对角色的认识;另一方面《社交网络》在现实经历基础上加工创造,塑造了极为优秀的银幕形象,使得其跳脱了传记电影的类型,成为跨青春片、商战片的类型电影。《社交网络》采用的非典型的传记影片拍摄手法也展示了大卫·芬奇一贯的美学风格,电影借助平实的人物塑造和巧妙的镜头语言,向观众揭示了美国当代资本社会环境中一代年轻人的无意识状态与价值取向。

解读《社交网络》的电影创作特色

电影《社交网络》赢得了众多影迷们的喜爱,它成功的原因有很多,其中非常重要的一点是它在电影创作上独具特色。该电影采用了多人物多视角叙事方式,使观众在深入人物心理的同时又能保持作为观众的中立立场。蒙太奇手法的高超运用使它无愧于奥斯卡最佳电影剪辑的称号。主要人物的后现代主义形象深入契合当今社会一系列话题,使它在为观众呈上一顿艺术大餐的同时又引起人们对这些话题的深思。

《社交网络》:成功背后的人性反思

电影《社交网络》取材于当前最流行社交网站之一Facebook创始人马克·扎克伯格的故事,改编自《意外的亿万富翁：Facebook的创立,一个关于性、金钱、天才和背叛的故事》。经典的作品总是让人回味无穷,《社交网络》这部电影让我们以独特的方式领略了天才成功记,更让我们对现代社会人情关系反思无尽,尤其是让我们对人性的扭曲发出无奈的唏嘘感叹。

《社交网络》的后现代主义研究

由大卫·芬奇执导,改编自麦兹里奇小说的影片《社交网络》一经上映就赢得了口碑、票房、奖项的三丰收。获得了奥斯卡、金像奖等149个奖项。这显然是大卫·芬奇从影以来不菲的成绩。从故事脉络上来看,《社交网络》讲述的是旷世奇才马克·扎尔伯格和他的伙伴是如何建立和发展Facebook的发家史。虽然《社交网络》是一部传记电影,但影片中的文化意义和感情元素更为深刻,故事的叙述视角也独树一帜。影片以人际关系为切入点,讲述了电影中的人物是如何经历从亲密到陌生再到对峙这样的一个过程,这是从马克·扎尔伯格的情感抛物线上抛出一个个赋予人性哲理的深度问题。这也是“人性实验大师”大卫·芬奇独特的文本风格。

大卫·芬奇电影作品中的黑色元素、元叙事文本与多重话语建构

大卫·芬奇最初在美国因拍摄音乐MV短片闻名,在执导《异形3》(1992)后进入一线电影导演行列,由于执导了《七宗罪》(1995)、《搏击俱乐部》(1999)、《社交网络》(2010)等大量悬疑与奇幻类型的电影作品,成为当今好莱坞最具有影响力的导演之一。大卫·芬奇在业内以对画面与人物的精致乃至苛刻的掌控出名,他擅长利用黑色元素制造出多重效果。

马克·扎克伯格 混蛋的成功哲学

扎克伯格22岁时,已经是世界上最年轻的亿万富翁。他成功的方式可能确实像电影《社交网络》所描写的那样,有些"混蛋"。但无论如何,扎克伯格已经取代比尔·盖茨和乔布斯,成为改变我们生活方式最重要的人。

A New Evaluation Algorithm for the Influence of User in Social Network

Online social networks have gradually permeated into every aspect of people's life.As a research hotspot in social network, user influence is of theoretical and practical significant for information transmission, optimization and integration. A prominent application is a viral marketing campaign which aims to use a small number of targeted infl uence users to initiate cascades of infl uence that create a global increase in product adoption. In this paper, we analyze mainly evaluation methods of user infl uence based on IDM evaluation model, Page Rank evaluation model, use behavior model and some other popular influence evaluation models in currently social network. And then, we extract the core idea of these models to build our influence evaluation model from two aspects, relationship and activity. Finally, the proposed approach was validated on real world datasets,and the result of experiments shows that our method is both effective and stable.

Social network search based on semantic analysis and learning

Because of everyone＇s involvement in social networks, social networks are full of massive multimedia data, and events are got released and disseminated through social networks in the form of multi-modal and multi-attribute heterogeneous data. There have been numerous researches on social network search. Considering the spatio-temporal feature of messages and social relationships among users, we summarized an overall social network search framework from the perspective of semantics based on existing researches. For social network search, the acquisition and representation of spatio-temporal data is the basis, the semantic analysis and modeling of social network cross-media big data is an important component, deep semantic learning of social networks is the key research field, and the indexing and ranking mechanism is the indispensable part. This paper reviews the current studies in these fields, and then main challenges of social network search are given. Finally, we give an outlook to the prospect and further work of social network search.

Mitigation Strategy against Cascading Failures on Social Networks

Cascading failures are common phenomena in many of real-world networks,such as power grids,Internet,transportation networks and social networks.It's worth noting that once one or a few users on a social network are unavailable for some reasons,they are more likely to influence a large portion of social network.Therefore,an effective mitigation strategy is very critical for avoiding or reducing the impact of cascading failures.In this paper,we firstly quantify the user loads and construct the processes of cascading dynamics,then elaborate the more reasonable mechanism of sharing the extra user loads with considering the features of social networks,and further propose a novel mitigation strategy on social networks against cascading failures.Based on the realworld social network datasets,we evaluate the effectiveness and efficiency of the novel mitigation strategy.The experimental results show that this mitigation strategy can reduce the impact of cascading failures effectively and maintain the network connectivity better with lower cost.These findings are very useful for rationally advertising and may be helpful for avoiding various disasters of cascading failures on many real-world networks.

Point-of-Interest Recommendation in LocationBased Social Networks with Personalized Geo-Social Influence

Point-of-interest(POI) recommendation is a popular topic on location-based social networks(LBSNs).Geographical proximity,known as a unique feature of LBSNs,significantly affects user check-in behavior.However,most of prior studies characterize the geographical influence based on a universal or personalized distribution of geographic distance,leading to unsatisfactory recommendation results.In this paper,the personalized geographical influence in a two-dimensional geographical space is modeled using the data field method,and we propose a semi-supervised probabilistic model based on a factor graph model to integrate different factors such as the geographical influence.Moreover,a distributed learning algorithm is used to scale up our method to large-scale data sets.Experimental results based on the data sets from Foursquare and Gowalla show that our method outperforms other competing POI recommendation techniques.

User Identification Based on Multiple Attribute Decision Making in Social Networks

Social networks are becoming increasingly popular and influential,and users are frequently registered on multiple networks simultaneously,in many cases leaving large quantities of personal information on each network.There is also a trend towards the personalization of web applications;to do this,the applications need to acquire information about the particular user.To maximise the use of the various sets of user information distributed on the web,this paper proposes a method to support the reuse and sharing of user profiles by different applications,and is based on user profile integration.To realize this goal,the initial task is user identification,and this forms the focus of the current paper.A new user identification method based on Multiple Attribute Decision Making(MADM) is described in which a subjective weight-directed objective weighting,which is obtained from the Similarity Weight method,is proposed to determine the relative weights of the common properties.Attribute Synthetic Evaluation is used to determine the equivalence of users.Experimental results show that the method is both feasible and effective despite the incompleteness of the candidate user dataset.

How Do Companies Achieve Their Marketing Goals With Social Networks？

This work examines the role of social network sites as a tool used by companies to achieve marketing goals. As known from the main business literature, the social network represents one of the most important instrument to improve the company fame by strengthening the affection of customers to the brand. For this reason, some companies use these tools to build relations and contacts with customers all over the world. The population of social networks users is made, for the most parts, of youngsters （people belonging to the 13-30 years old cluster）. In the last years, with the social web networking, social communication lost the exclusive social meaning and social network sites become strategic instruments for the construction of powerful relations that connect people with people and people with firms. This work is aimed at clarifying the genesis and the evolution of the relations between companies and potential customers, focusing on the tools used by the firm to achieve their marketing goals through social network sites （SNSs）. First of all, the work proposes the recognition of some studies about the origin of web social network and their links with marketing strategies. Secondly, it considers marketing goals achieved from any companies through social networking with a particular focus on advertising through web social networking.

New Media, Public Sphere, and Arab Spring： Demystifying the Power of Social Networks

This paper looks at the new media, communication, and political environment in both Tunisia and Egypt during and after the revolution. The new environment provided activists, politicians, civil society, and youth among others, who want to express their opinions and share their views, with various channels and means of corranunication to be part of the political action and to participate in the decision-making process. Social media played an important role in mobilizing youth to rally and protest. This is to say that a new model of communication has emerged with this new environment. The receiver has become the sender and the producer of the message. The process of communication, therefore, has been changed from one to many to from many to many, and everybody became sender and receiver at the same time. The main research question this paper aims to answer is： Are social networks enough to change the political and economic scene in the Arab World？ And is there a relationship between the new communication environment and Arab spring？ The year 2011 has been in the Arab world the year of social networks and radical changes in the political scene where a score of dictators were ousted. New political communication networks and mechanisms took place, and for the first time in Arab political communication, public opinion was a major political player. Social networks helped tremendously the formation of new public sphere where the public finds its way in the media and communication processes. At their best, new media can mobilize crowds and masses to rally and protest. They can give a social perspective to movements. However, they can＇t make change and implement democracy. After the collapse of the regimes in Tunisia and Egypt, things are not getting any better. There is no democratic transition, and both countries are experiencing complex economic, social, and political problems.

Mobile Social Networking Aided Content Dissemination in Heterogeneous Networks

Since more and more mobile applications are based on the proliferation of social information, the study of Mobile Social Networks （MSNs） combines social sciences and wireless communications. Operating wireless networks more efficiently by exploiting social relationships between MSN users is an appealing but challenging option for network operators. An MSN-aided content dissemination technique is presented as a potential extension of conventional cellular wireless networks in order to satisfy growing data traffic. By allowing the MSN users to create a self-organized ad hoc network for spontaneously disseminating contents, the network operator may be able to reduce the operational costs and simultaneously achieve an improved network performance. In this paper, we first summarize the basic features of the MSN architecture, followed by a survey of the factors which may affect MSN-aided content dissemination. Using a case study, we demonstrate that one can save resources of the Base Station （BS） while substantially lowering content dissemination delay. Finally, other potential applications of MSN-aided content dissemination are introduced, and a range of lustre challenges are summarized.

Internet Addiction： Just Facebook Me! The Role of Social Networking Sites in Internet Addiction

Internet based social-networking sites like Facebook are highly attractive, user-friendly, and increasingly popular. Current estimates indicate over 750 million users of Facebook alone. However, Internet addiction is an increasing problem amongst today＇s youth and as yet, is understudied in the United States. This study looked at the relationship between this new social-networking tool and the increasing phenomenon of internet addiction symptoms using both a US college sample （age 19years） and a US high-school sample （age 14years）. Findings indicate that SNS （Social Networking Site） activity maybe more predictive of addictive behaviors than general internet use and that higher percents of symptomology occur in those users reporting SNS activity as their primary internet activity.

Social Networking With a Purpose

Online dating sites are growing steadily in popularity, despite challenging economic times. In addition, online dating sites are facing increasing competition for their services from free social networking sites. Despite these harsh economic times and the increasing competition, online dating websites have continued to increase in popularity. This growth justifies the need to better understand how these volitional and paid websites have been so successful. By addressing the call for research in emergent information systems （IS） contexts, this study proposes a theoretical framework for investigation in a purely volitional website context. A framework based on the DeLone and McLean＇s IS success model is developed. Implications for practice and research are discussed.

Collective Background Extraction for Station Market Area by Using Location Based Social Network

Half centuries of follow-up survey has enabled the architects and urban planners to design rationally by the aid of planning Nonetheless, limitation has occurred at planning because city has been changing its utility in accordance with its users＇ demand. In this paper, the authors proposed a method to analyze trait of users in market areas near stations by analyzing location based social network. After the datum collection from geotagged tweets, these GPS （global positioning system） datum were plotted to map attained from yahoo open location platform. Then the morphological analysis and terminology extraction system extracted the keywords and their scores. After calculating the distance from stations and users＇ GPS coordination, the authors extracted the array of keywords and corresponding scores in some station market area. Lastly, ratios of all users＇ scores and city＇s scores were calculated to examine the locality. Full combination of data collection, natural language processing and visualization enabled the authors to envisage distribution of collective background in city.

Online Social Support and Use of SNSs Among College Students Relationship to Online and Offiine Social Skills

The subjects of this study are college students aged between 18 to 26 years old from different majors. Investigated the use intensity and addiction of SNSs among college students, with variables of use behaviors and online social support are relate to their online social skills and offline social skills. Seven point Likert scale, descriptive statistics, One-way ANOVA and logistic regression were used to determine the correlations of different use intensities and levels of addiction. The results explored whether college students＇ online social skills, offline social skills, and online social support are correlated with use intensity and addiction. Long-term or high-frequency use of SNSs does not lead to equivalent social relationships on SNSs, yet addiction to SNSs can reflect the positive support and communication ability of college students in online interpersonal relationships.

Facebook改名Meta背后的元宇宙品牌愿景

偏执、自负、孤僻、难以捉摸……这是许多人对Facebook创办人扎克伯格的评价。这种评论容易掩盖扎克伯格性格中的另一些特质,比如:果断、迅速、坚持……扎克伯格成名甚早,好莱坞以他为原型创作了影片《社交网络》,电影中的扎克伯格就是以上这些性格特质的神奇综合体。

Learning embeddings of a heterogeneous behavior network for potential behavior prediction

Potential behavior prediction involves understanding the latent human behavior of specific groups,and can assist organizations in making strategic decisions.Progress in information technology has made it possible to acquire more and more data about human behavior.In this paper,we examine behavior data obtained in realworld scenarios as an information network composed of two types of objects(humans and actions)associated with various attributes and three types of relationships(human-human,human-action,and action-action),which we call the heterogeneous behavior network(HBN).To exploit the abundance and heterogeneity of the HBN,we propose a novel network embedding method,human-action-attribute-aware heterogeneous network embedding(a4 HNE),which jointly considers structural proximity,attribute resemblance,and heterogeneity fusion.Experiments on two real-world datasets show that this approach outperforms other similar methods on various heterogeneous information network mining tasks for potential behavior prediction.