Social Streams Research Articles

Evolutionary Network Analysis

Evolutionary network analysis has found an increasing interest in the literature because of the importance of different kinds of dynamic social networks, email networks, biological networks, and social streams. When a network evolves, the results of data mining algorithms such as community detection need to be correspondingly updated. Furthermore, the specific kinds of changes to the structure of the network, such as the impact on community structure or the impact on network structural parameters, such as node degrees, also needs to be analyzed. Some dynamic networks have a much faster rate of edge arrival and are referred to as network streams or graph streams. The analysis of such networks is especially challenging, because it needs to be performed with an online approach, under the one-pass constraint of data streams. The incorporation of content can add further complexity to the evolution analysis process. This survey provides an overview of the vast literature on graph evolution analysis and the numerous applications that arise in different contexts.

Call for Papers for the Social Finance and Sustainable Finance Stream: The 14th Finance, Risk and Accounting Perspectives Conference Oriel College, University of Oxford 22nd–24th September 2014 Conference pages http://www.acrn.eu/finance

Call for Papers for the Social Finance and Sustainable Finance Stream: The 14th Finance, Risk and Accounting Perspectives Conference Oriel College, University of Oxford 22nd–24th September 2014 Conference pages http://www.acrn.eu/finance

Discovering Emerging Topics in Social Streams via Link-Anomaly Detection

Detection of emerging topics is now receiving renewed interest motivated by the rapid growth of social networks. Conventional-term-frequency-based approaches may not be appropriate in this context, because the information exchanged in social-network posts include not only text but also images, URLs, and videos. We focus on emergence of topics signaled by social aspects of theses networks. Specifically, we focus on mentions of users--links between users that are generated dynamically (intentionally or unintentionally) through replies, mentions, and retweets. We propose a probability model of the mentioning behavior of a social network user, and propose to detect the emergence of a new topic from the anomalies measured through the model. Aggregating anomaly scores from hundreds of users, we show that we can detect emerging topics only based on the reply/mention relationships in social-network posts. We demonstrate our technique in several real data sets we gathered from Twitter. The experiments show that the proposed mention-anomaly-based approaches can detect new topics at least as early as text-anomaly-based approaches, and in some cases much earlier when the topic is poorly identified by the textual contents in posts.

Effective Browsing Technique based on Behavioral Collaborative Filtering on Social Streams

In recent years, Social Networking Services (SNSs) are growing in popularity, and generating new articles moment by moment. However, when huge article streams are delivered from the SNS, it is not easy to browse them efficiently because users would sometimes skip valuable articles. In this paper, we propose a method to recommend an unread article in order to achieve efficient browsing. Our method estimates the preference of a user on a delivered article based on the browsing behavior of the user, and predicts the preference of each unread article based on the collaborative filtering approach. Our system estimates the value of each unread article for the target user based on the behaviors of users who might be highly similar to the target user's behavior of reading articles, and utilizes the estimation results for composing unread articles into a stream in an appropriate order to realize efficient browsing.

Sensing Trending Topics in Twitter

Online social and news media generate rich and timely information about real-world events of all kinds. However, the huge amount of data available, along with the breadth of the user base, requires a substantial effort of information filtering to successfully drill down to relevant topics and events. Trending topic detection is therefore a fundamental building block to monitor and summarize information originating from social sources. There are a wide variety of methods and variables and they greatly affect the quality of results. We compare six topic detection methods on three Twitter datasets related to major events, which differ in their time scale and topic churn rate. We observe how the nature of the event considered, the volume of activity over time, the sampling procedure and the pre-processing of the data all greatly affect the quality of detected topics, which also depends on the type of detection method used. We find that standard natural language processing techniques can perform well for social streams on very focused topics, but novel techniques designed to mine the temporal distribution of concepts are needed to handle more heterogeneous streams containing multiple stories evolving in parallel. One of the novel topic detection methods we propose, based on -grams cooccurrence and topic ranking, consistently achieves the best performance across all these conditions, thus being more reliable than other state-of-the-art techniques.

Automatic extraction of persistent topics from social text streams

Microblogging services allow users to publish their thoughts, activities, and interests in the form of text streams and to share them with others in a social network. A user's text stream in a microblogging service is temporally composed of the posts the user has written or republished from other socially connected users. In this context, most research on the microblogging service has primarily focused on social graph or topic extraction from the text streams, and in particular, several studies attempted to discover user's topics of interests from a text stream since the topics play a crucial role in user search, friend recommendation, and contextual advertisement. Yet, they did not yet fully address unique properties of the stream. In this paper, we study a problem of detecting the topics of long-term steady interests to a user from a text stream, considering its dynamic and social characteristics, and propose a graph-based topic extraction model. Extensive experiments have been carried out to investigate the effects of the proposed approach by using a real-world dataset, and the proposed model is shown to produce better performance than the existing alternatives.

Towards Cross-Domain Learning for Social Video Popularity Prediction

Previous research on online media popularity prediction concluded that the rise in popularity of online videos maintains a conventional logarithmic distribution. However, recent studies have shown that a significant portion of online videos exhibit bursty/sudden rise in popularity, which cannot be accounted for by video domain features alone. In this paper, we propose a novel transfer learning framework that utilizes knowledge from social streams (e.g., Twitter) to grasp sudden popularity bursts in online content. We develop a transfer learning algorithm that can learn topics from social streams allowing us to model the social prominence of video content and improve popularity predictions in the video domain. Our transfer learning framework has the ability to scale with incoming stream of tweets, harnessing physical world event information in real-time. Using data comprising of 10.2 million tweets and 3.5 million YouTube videos, we show that social prominence of the video topic (context) is responsible for the sudden rise in its popularity where social trends have a ripple effect as they spread from the Twitter domain to the video domain. We envision that our cross-domain popularity prediction model will be substantially useful for various media applications that could not be previously solved by traditional multimedia techniques alone.

TeRec

As social media further integrates into our daily lives, people are increasingly immersed in real-time social streams via services such as Twitter and Weibo. One important observation in these online social platforms is that users' interests and the popularity of topics shift very fast, which poses great challenges on existing recommender systems to provide the right topics at the right time. In this paper, we extend the online ranking technique and propose a temporal recommender system - TeRec. In TeRec, when posting tweets, users can get recommendations of topics (hashtags) according to their real-time interests, they can also generate fast feedbacks according to the recommendations. TeRec provides the browser-based client interface which enables the users to access the real time topic recommendations, and the server side processes and stores the real-time stream data. The experimental study demonstrates the superiority of TeRec in terms of temporal recommendation accuracy.

Event detection over twitter social media streams

In recent years, microblogs have become an important source for reporting real-world events. A real-world occurrence reported in microblogs is also called a social event. Social events may hold critical materials that describe the situations during a crisis. In real applications, such as crisis management and decision making, monitoring the critical events over social streams will enable watch officers to analyze a whole situation that is a composite event, and make the right decision based on the detailed contexts such as what is happening, where an event is happening, and who are involved. Although there has been significant research effort on detecting a target event in social networks based on a single source, in crisis, we often want to analyze the composite events contributed by different social users. So far, the problem of integrating ambiguous views from different users is not well investigated. To address this issue, we propose a novel framework to detect composite social events over streams, which fully exploits the information of social data over multiple dimensions. Specifically, we first propose a graphical model called location-time constrained topic (LTT) to capture the content, time, and location of social messages. Using LTT, a social message is represented as a probability distribution over a set of topics by inference, and the similarity between two messages is measured by the distance between their distributions. Then, the events are identified by conducting efficient similarity joins over social media streams. To accelerate the similarity join, we also propose a variable dimensional extendible hash over social streams. We have conducted extensive experiments to prove the high effectiveness and efficiency of the proposed approach.

Building Bridges: Constructing Social Enterprise Curriculum in the Humanities

Creating an innovative suite of courses within the Bachelor of Arts has required the development of a complex pedagogy, particularly when the needs of the context require an interdisciplinary approach. This paper, which utilises reflection on practice as its methodology, explores the Social Enterprise core stream which has been a significant element of study since 2008. While the paper deals with some of the particular circumstances of introducing practice learning to traditional theoretical disciplines, it is most concerned with the pedagogical strength of combining inquiry based learning with problem based learning, to lead to work integrated learning, and developing reflective practice to integrate all. Since 2008, the School of Humanities at Griffith University has incorporated a Social Enterprise signature experience into the Bachelor of Arts. Broadly, social enterprises are distinguished by their pursuit of community wealth in the marketplace to pursue their aims. They pursue a triple bottom line of social, economic and environmental prosperity. Griffith University is located in South East Queensland, Australia and is well regarded as both a research university and for its development of highly innovative programmes. Approximately 40, 000 students are enrolled over five campuses. In the Bachelor of Arts, we also use the verb form, 'socially enterprising' to invite our students to be innovative, creative and empowered, regardless of the economic sector where they find employment. Thus our work at Griffith University is underpinned by a pedagogical ethic and imperative to excite our students about their own prospects for being a part of change, based on a thorough and ongoing engagement with people and organisations in the 'real world' who are already moving and shaking. This has meant that a curriculum has had to be developed which both presents the underlying issues and the third sector approaches and interpolates these studies into a multi-disciplinary context. This signature experience consists of six semester-long units, presented sequentially, and includes a third year professional placement in the Third Sector. The final semester capstone subject enables students to both reflect upon their experience of the degree and to plan and manage a showcase event. The first year units focus upon the development of communication and critical thinking skills, and the introduction of critical issues relevant to the Third Sector such as human rights and social justice. Alongside an initial exploration of the history and practice of the Third Sector, these first year courses are designed to incite a broader awareness of the reason for choosing a life that contributes to the wider community. The second year units are concerned with the consolidation of an ethical foundation and developing skills required in the workplace in this field.

Reports on the Workshops Held at the Sixth International AAAI Conference on Weblogs and Social Media

The workshops day at the Sixth International Conference on Weblogs and Social Media included three full‐day workshops (Real‐Time Analysis and Mining of Social Streams, Social Media Visualization, and When the City Meets the Citizen) and one half‐day workshop (The Potential of Social Media Tools and Data for Journalists in the News Media Industry). Workshops were held on June 4, 2012, the day prior to the first day of the technical conference, in Dublin, Ireland.

공공공간에서 나타나는 미디어 특성에 관한 연구 - 뉴 미디어와 HCI 이론을 중심으로 -

With digital technology, space design is developing in a new direction with the changing paradigm. The space creates an interactive environment by motivating the User's active participation through the digital madia. In this social stream, it is very important to think about how this new paradigm affects the spatial design and the interactions between social changes and spatial design paradigm, so that we can understand design paradigm of our time. Hence, in this research, we will think about social characteristic and design paradigm of digital age by questioning how spatial design is changing in the digital age and how digital technology is affecting spatial design. this study analyzed about the space form, digital media setting, user interactivity of the examples of experience space using digital media. fields of our society, interactive space with the concept of HCI became a big issue in environmental design field. In this interactive space, various types of informative factors of the given space are sent using sensor and computer networking technology to the main system, and the main computer system sends manipulated output media to interactive devices. So, a user's movement in the space is more than just a movement itself user's movement now forms a important spatial structure that leads the narrative of the space. Researcher will analyze the characteristic of a public space and progress this research supposing that space needs this interactive design.

Social stream marketing on Facebook: a case study

Recently, social network marketing has gained tremendously in popularity. There are increasing numbers of web-based companies that focus their marketing strategies on social network platforms such as Facebook, Twitter, etc. Even if social network marketing is perceived as a huge success, little or nothing is known about how well such social network-based marketing campaigns perform. To contribute to this field of research, we present in this paper the results of an ad-driven social network-based marketing campaign centred on the social network Facebook. In particular, we demonstrate in the extent to which ads placed on the user’s social stream and generated by the Facebook tools and applications can increase the number of visits, profit or ROI of a web-based platform called VirWoX. In addition to these findings, we present an analysis of a number of simple real-time measures to detect the most ‘valuable’ users on Facebook. To the best of our knowledge, this is the first work that provides such detailed results of a social stream marketing campaign using Facebook. This paper is relevant for engineers, researchers or teachers who are interested in the field of social media marketing.

Personalizing of Content Dissemination in Online Social Networks

Online social networks have seen a rapid growth in recent years. A key aspect of many of such networks is that they are rich in content and social interactions. Users of social networks connect with each other and forming their own communities. With the evolution of huge communities hosted by such websites, users suffer from managing information overload and it is become hard to extract useful information. Thus, users need a mechanism to filter online social streams they receive as well as enable them to interact with most similar users. In this paper, we address the problem of personalizing dissemination of relevant information in knowledge sharing social network. The proposed framework identifies the most appropriate user(s) to receive specific post by calculating similarity between target user and others. Similarity between users within OSN is calculated based on users’ social activity which is an integration of content published as well as social pattern Application of this framework to a representative subset of a large real-world social network: the user/community network of the blog service stack overflow is illustrated here. Experiments show that the proposed model outperform tradition similarity methods.

Social streams based on network proximity

This paper describes a new approach for using wireless sensors on mobile phones for integrating data from social networks. We describe existing models for integrating sensors and social networks, as well as propose a new practical approach for social context-aware data discovery that uses mobile phone as proximity sensor. Our concept uses new model for location-related statuses (check-ins) based on network proximity rules. And an appropriate mobile service (context-aware browser client for social networks) can present that information to mobile subscribers. As the potential use-cases for the proposed approach we can mention all projects related to hyper-local news data. For example, proximity marketing, Smart City news, indoor information delivery, etc.

Redesigning a Large Supply Chain Management System to Reduce the Government Administration: A Socio-Functional Systems Approach

Redesigning managerial structure and redefining managerial processes in a large supply chain network in national scale is the main focus in this study. The considered supply chain is mainly under governmental management. Reducing the role of the government in managing the supply chain is a strategy pursued in this study. The supply chain is approached as a socioeconomic system and a methodology is designed to address important aspects of the system. The methodology is divided into two streams addressing two main aspects of a socioeconomic system—functional and social. Organizational cybernetics is the core of functional stream. The SCOR model has been used as a well-accepted supply chain management tool alongside the viable system model. The Social stream benefits from ideas of the methods which are used in the soft systems methodology and interactive planning. The methodology is applied in the considered supply chain network in which the final product is chicken meat. While supply chain management is mostly approached from a functional viewpoint, this study also considers its social aspects. Using soft methods as well as functional methods result in a systemic design which is functionally and socially desirable.

Enriching user search experience by mining social streams with heuristic stones and associative ripples

Recently, social networking sites such as Facebook and Twitter are becoming increasingly popular. The high accessibility of these sites has allowed the so-called social streams being spread across ...

Democratizing health. Consumer groups in the policy process

DEMOCRATIZING HEALTH. CONSUMER GROUPS IN THE POLICY PROCESS Edited by Hans Lofgren, Evelyne de Leeuw and Michael Leahy 2011 Edward Elgar. ISBN 978 1 84844 784 4 10.1071/AHv36n3_BR1One of the greatest strengths of this book is the quite remarkable spread of contributors from across the globe. The three editors - all from our own Deakin University - are to be congratulated for managing to get such a broad international array of authors and country experiences. And these matter for such a book. They matter first because the issue of democratising health is a genuinely international one; second in any country's agenda for pursuing such democratisation there are lessons to be learned from other countries; and third, as it turns out, experiences across countries vary quite a bit.I enjoyed the book and found it a most useful addition to the literature in this field. In reviewing it, however, I need to declare a particular bias with respect to democratising health. I see citizens as being those who would be involved in such a process and I prefer to draw a clear distinction between citizens and consumers. (I will return to that issue shortly.)The book, for an edited volume with 16 chapters, is very readable. That is quite something when it covers such a range of very different countries from the USA to Malaysia, from Austria to Australia.The book opens with the following statement from the editors:'This book examines the extent to which consumer groups engage in the development of policy affecting their members' health and health care. Such engagement may be referred to as the 'democratisation of health' but, as the contributions to this book show, there are considerable differences between national contexts as to what this means, both in theory and in practice.' (p. 1)The editors suggest that there are two streams to democracy 'the liberal or the social stream' but that, whichever is adopted, democracy 'is perceived rightly or wrongly as the only form of government capable of giving due recognition to human dignity'. (p. 2)Beyond the introductory chapter, Milewa discusses health activism in the age of governance and interestingly concludes that 'health activist groups exist only because their aims have not been met in the context of the political, bureaucratic and medical status quo.' (p. 27)The majority of the other chapters have a specific country focus. For Malaysia, Barraclough and Kai Lit show how, in the wake of the adoption of neo-liberal ideology and policies, including privatisation, the role of consumer groups changed. 'Their role in monitoring 'value for money' and quality of care was intensified by the rapid growth of private hospitals and the more intensive use of medical technology' (p. 164). It was then perhaps inevitable that they became embroiled in 'an ideological challenge to the government's stated goals of reducing the public financing of health care and privatising the public agencies responsible for its delivery' (p. 164).Church and Armstrong worry about the role of citizens in Canada generally, but also specifically with respect to healthcare where they claim that consumer groups have increasingly been driven into 'an unholy alliance with private corporate concerns' (p. 205) and they call for 'a greater sense of organic citizenship' (p. 205) in Canada.There are two chapters on the USA, one by Fox and Lambertson is quite despairing of the role of health consumers to date - but they take heart from the Obama reforms that their voice can make a difference; they end on a positive note, 'If a strong consumer voice continues to develop...this nascent voice [can] gradually weave its way into the fabric of American political dialogue' (p. …

Socialized ubiquitous personal study: Toward an individualized information portal

Recently, SNS (Social Network Service), blog and microblog have become very popular. Stream data, a large collection of diverse contents that are created dynamically in the form of streams, have become an important part of the Internet resources. At the same time, it has become easier to collect peopleʼs activities as their lifelogs, not only in the cyber space, but also in the physical world by means of ubiquitous and sensing technology. Either stream data or lifelogs represent different aspects of peopleʼs information behaviors and social activities, which we call Social Streams. In this study, we try to integrate and organize these social stream data, such as Twitter Tweets, into Ubiquitous Personal Study (UPS) proposed in our previous study. In this paper, we introduce and define a set of new metaphors: Drop, Stream, River and Ocean, to represent a variety of social stream data in different stages, in order to enable UPS socialized toward an individualized information portal. We further propose a Framework of Organic Streams to meaningfully organize these stream data. We discuss the design and implementation issues of a prototype system, and describe the algorithms to realize our proposed metaphors. Moreover, we show a scenario of using the socialized UPS to support learning activities, with experimental data and analysis results.

From TV to Twitter: How Ambient News Became Ambient Journalism

Scholars have applied the term "ambient" to journalism to describe the omnipresent nature of news in society through the proliferation of one-way media into public spaces. This approach is based on a one-directional model of mass media where the audience is framed as the receptor of communication. However this paper suggests that we need to reassess the meaning of ambient as applied to news and journalism due to the participatory and interactive characteristics of the networked digital media. The Internet has changed the relationship between journalists and audiences from a one-way, asymmetric model of communication to a more participatory and collective system, where citizens have the ability to participate in the news production process. This paper argues that ambient news has evolved into ambient journalism – an awareness system that offers diverse means to collect, communicate, share and display news and information, from both professional and non-professional sources.