@article{batagelj2011algorithms,
abstract = {The structure of a large network (graph) can often be revealed by partitioning it into smaller and possibly more dense sub-networks that are easier to handle. One of such decompositions is based on “},
author = {Batagelj, Vladimir and Zaveršnik, Matjaž},
doi = {10.1007/s11634-010-0079-y},
interhash = {a0bd7331f81bb4da72ce115d5943d6e4},
intrahash = {cd0d5266688af6bb98bde7f99e3a54c1},
issn = {1862-5347},
journal = {Advances in Data Analysis and Classification},
language = {English},
number = 2,
pages = {129--145},
publisher = {Springer},
title = {Fast algorithms for determining (generalized) core groups in social networks},
url = {http://dx.doi.org/10.1007/s11634-010-0079-y},
volume = 5,
year = 2011
}
@article{sun2013social,
abstract = {The birth and decline of disciplines are critical to science and society. How do scientific disciplines emerge? No quantitative model to date allows us to validate competing theories on the different roles of endogenous processes, such as social collaborations, and exogenous events, such as scientific discoveries. Here we propose an agent-based model in which the evolution of disciplines is guided mainly by social interactions among agents representing scientists. Disciplines emerge from splitting and merging of social communities in a collaboration network. We find that this social model can account for a number of stylized facts about the relationships between disciplines, scholars, and publications. These results provide strong quantitative support for the key role of social interactions in shaping the dynamics of science. While several “science of science” theories exist, this is the first account for the emergence of disciplines that is validated on the basis of empirical data.},
author = {Sun, Xiaoling and Kaur, Jasleen and Milojevic, Stasa and Flammini, Alessandro and Menczer, Filippo},
doi = {10.1038/srep01069},
interhash = {5cd31392e997555d78596f962044f84b},
intrahash = {721dcd5644cca27fd50d8e6ffd667056},
journal = {Scientific Reports},
month = jan,
publisher = {Macmillan Publishers Limited},
title = {Social Dynamics of Science},
url = {http://dx.doi.org/10.1038/srep01069},
volume = 3,
year = 2013
}
@article{barabsi2013network,
abstract = {Professor Barabási's talk described how the tools of network science can help understand the Web's structure, development and weaknesses. The Web is an information network, in which the nodes are documents (at the time of writing over one trillion of them), connected by links. Other well-known network structures include the Internet, a physical network where the nodes are routers and the links are physical connections, and organizations, where the nodes are people and the links represent communications.},
author = {Barabási, Albert-László},
doi = {10.1098/rsta.2012.0375},
eprint = {http://rsta.royalsocietypublishing.org/content/371/1987/20120375.full.pdf+html},
interhash = {e2cfdd2e3c7c68581e3ab691909ed28b},
intrahash = {208c1f9d6d8eff67cee07ebdf3cd0fc1},
journal = {Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences},
number = 1987,
title = {Network science},
url = {http://rsta.royalsocietypublishing.org/content/371/1987/20120375.abstract},
volume = 371,
year = 2013
}
@article{robertson2013programming,
abstract = {The aim of ‘programming the global computer’ was identified by Milner and others as one of the grand challenges of computing research. At the time this phrase was coined, it was natural to assume that this objective might be achieved primarily through extending programming and specification languages. The Internet, however, has brought with it a different style of computation that (although harnessing variants of traditional programming languages) operates in a style different to those with which we are familiar. The ‘computer’ on which we are running these computations is a social computer in the sense that many of the elementary functions of the computations it runs are performed by humans, and successful execution of a program often depends on properties of the human society over which the program operates. These sorts of programs are not programmed in a traditional way and may have to be understood in a way that is different from the traditional view of programming. This shift in perspective raises new challenges for the science of the Web and for computing in general.},
author = {Robertson, David and Giunchiglia, Fausto},
doi = {10.1098/rsta.2012.0379},
eprint = {http://rsta.royalsocietypublishing.org/content/371/1987/20120379.full.pdf+html},
interhash = {c671d953e4eb09fc3fe67f93ccd2024c},
intrahash = {a802922683b23455f903551ee2b24b42},
journal = {Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences},
month = mar,
number = 1987,
title = {Programming the social computer},
url = {http://rsta.royalsocietypublishing.org/content/371/1987/20120379.abstract},
volume = 371,
year = 2013
}
@article{kleinberg2013analysis,
abstract = {The growth of the Web has required us to think about the design of information systems in which large-scale computational and social feedback effects are simultaneously at work. At the same time, the data generated by Web-scale systems—recording the ways in which millions of participants create content, link information, form groups and communicate with one another—have made it possible to evaluate long-standing theories of social interaction, and to formulate new theories based on what we observe. These developments have created a new level of interaction between computing and the social sciences, enriching the perspectives of both of these disciplines. We discuss some of the observations, theories and conclusions that have grown from the study of Web-scale social interaction, focusing on issues including the mechanisms by which people join groups, the ways in which different groups are linked together in social networks and the interplay of positive and negative interactions in these networks.},
author = {Kleinberg, Jon},
doi = {10.1098/rsta.2012.0378},
eprint = {http://rsta.royalsocietypublishing.org/content/371/1987/20120378.full.pdf+html},
interhash = {b4686f01da53c975f342dbb40bdd1a90},
intrahash = {e3898cfb7206a7fee8eb3a5419aa030f},
journal = {Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences},
month = mar,
number = 1987,
title = {Analysis of large-scale social and information networks},
url = {http://rsta.royalsocietypublishing.org/content/371/1987/20120378.abstract},
volume = 371,
year = 2013
}
@book{dorling2012visualisation,
abstract = {How do you draw a map of 100,000 places, of more than a million flows of people, of changes over time and space, of different kinds of spaces, surfaces and volumes, from human travel time to landscapes of hopes, fears, migration, manufacturing and mortality? How do you turn the millions of numbers concerning some of the most important moments of our lives into images that allow us to appreciate the aggregate while still remembering the detail? The visualization of spatial social structure means, literally, making visible the geographical patterns to the way our lives have come to be s.},
address = {Hoboken},
author = {Dorling, Danny},
edition = {2nd},
interhash = {10af4174b8276fd3a604a88e03b5656b},
intrahash = {b024bc8aefe21e967777c3ebe62b5edb},
isbn = {9781118354001 1118354001},
publisher = {John Wiley & Sons},
refid = {796383238},
series = {Wiley Series in Computational and Quantitative Social Science},
title = {The Visualisation of Spatial Social Structure},
url = {http://public.eblib.com/EBLPublic/PublicView.do?ptiID=945112},
year = 2012
}
@article{maisonneuve2010participatory,
abstract = {Noise pollution is a major problem in cities around the world. The current methods to assess it neglect to represent the real exposure experienced by the citizens themselves, and therefore could lead to wrong conclusions and a biased representations. In this paper we present a novel approach to monitor noise pollution involving the general public. Using their mobile phones as noise sensors, we provide a low cost solution for the citizens to measure their personal exposure to noise in their everyday environment and participate in the creation of collective noise maps by sharing their geo-localized and annotated measurements with the community. Our prototype, called NoiseTube, can be found online [1].},
author = {Maisonneuve, Nicolas and Stevens, Matthias and Ochab, Bartek},
doi = {10.3233/IP-2010-0200},
interhash = {75f1760b3c55de573fffd69fcc10548e},
intrahash = {4dbb1ce355b7249bc2f66ed4b2126bab},
journal = {Information Polity},
month = jan,
number = 1,
pages = {51--71},
publisher = {IOS Press},
title = {Participatory noise pollution monitoring using mobile phones},
url = {http://dx.doi.org/10.3233/IP-2010-0200},
volume = 15,
year = 2010
}
@article{kanjo2010noisespy,
abstract = {In this paper we present the design, implementation, evaluation, and user experiences of the NoiseSpy application, our sound sensing system that turns the mobile phone into a low-cost data logger for monitoring environmental noise. It allows users to explore a city area while collaboratively visualizing noise levels in real-time. The software combines the sound levels with GPS data in order to generate a map of sound levels that were encountered during a journey. We report early findings from the trials which have been carried out by cycling couriers who were given Nokia mobile phones equipped with the NoiseSpy software to collect noise data around Cambridge city. Indications are that, not only is the functionality of this personal environmental sensing tool engaging for users, but aspects such as personalization of data, contextual information, and reflection upon both the data and its collection, are important factors in obtaining and retaining their interest.},
acmid = {1831011},
address = {Hingham, MA, USA},
author = {Kanjo, Eiman},
doi = {10.1007/s11036-009-0217-y},
interhash = {12b29df257d71dfd37193d6b4665004e},
intrahash = {387ebc6472794f598d07256a45f3d9b7},
issn = {1383-469X},
issue_date = {August 2010},
journal = {Mobile Networks and Applications},
month = aug,
number = 4,
numpages = {13},
pages = {562--574},
publisher = {Kluwer Academic Publishers},
title = {NoiseSPY: A Real-Time Mobile Phone Platform for Urban Noise Monitoring and Mapping},
url = {http://dx.doi.org/10.1007/s11036-009-0217-y},
volume = 15,
year = 2010
}
@book{pazosarias2012recommender,
address = {Berlin/Heidelberg},
doi = {10.1007/978-3-642-25694-3},
editor = {and Pazos Arias, José J. and Fernández Vilas, Ana and Díaz Redondo, Rebeca P.},
interhash = {56612672a3db5d6ea838e9bfa7b410cf},
intrahash = {aceda1417241eb872dc27db7c7e4158a},
isbn = {978-3-642-25693-6},
publisher = {Springer},
series = {Intelligent Systems Reference Library},
title = {Recommender Systems for the Social Web},
url = {http://link.springer.com/book/10.1007/978-3-642-25694-3/page/1},
volume = 32,
year = 2012
}
@inproceedings{pfaltz2012entropy,
abstract = {We introduce the concepts of closed sets and closure operators as mathematical tools for the study of social networks. Dynamic networks are represented by transformations. It is shown that under continuous change/transformation, all networks tend to "break down" and become less complex. It is a kind of entropy. The product of this theoretical decomposition is an abundance of triadically closed clusters which sociologists have observed in practice. This gives credence to the relevance of this kind of mathematical analysis in the sociological context. },
author = {Pfaltz, John L.},
booktitle = {Proceedings of the SOCINFO},
interhash = {753f13a5ffaa0946220164c2b05c230f},
intrahash = {044d0b1f6e737bede270a40bbddb0b06},
title = {Entropy in Social Networks},
year = 2012
}
@article{birkholz2012scalable,
abstract = {Studies on social networks have proved that endogenous and exogenous factors influence dynamics. Two streams of modeling exist on explaining the dynamics of social networks: 1) models predicting links through network properties, and 2) models considering the effects of social attributes. In this interdisciplinary study we work to overcome a number of computational limitations within these current models. We employ a mean-field model which allows for the construction of a population-specific socially informed model for predicting links from both network and social properties in large social networks. The model is tested on a population of conference coauthorship behavior, considering a number of parameters from available Web data. We address how large social networks can be modeled preserving both network and social parameters. We prove that the mean-field model, using a data-aware approach, allows us to overcome computational burdens and thus scalability issues in modeling large social networks in terms of both network and social parameters. Additionally, we confirm that large social networks evolve through both network and social-selection decisions; asserting that the dynamics of networks cannot singly be studied from a single perspective but must consider effects of social parameters. },
author = {Birkholz, Julie M. and Bakhshi, Rena and Harige, Ravindra and van Steen, Maarten and Groenewegen, Peter},
interhash = {a8ef0aac2eab74fc8eb3f9d3dc8a32dd},
intrahash = {aefcc2aa922b048bec85d5070494ed81},
journal = {CoRR},
month = sep,
title = {Scalable Analysis of Socially Informed Network Models: the data-aware mean-field approach },
url = {http://arxiv.org/abs/1209.6615},
volume = {abs/1209.6615},
year = 2012
}
@article{kautz1997referral,
acmid = {245123},
address = {New York, NY, USA},
author = {Kautz, Henry and Selman, Bart and Shah, Mehul},
doi = {10.1145/245108.245123},
interhash = {6995678b936b33eef9ea1396e53a1fc7},
intrahash = {832d16a8c86e769c7ac9ace5381f757e},
issn = {0001-0782},
issue_date = {March 1997},
journal = {Communications of the ACM},
month = mar,
number = 3,
numpages = {3},
pages = {63--65},
publisher = {ACM},
title = {Referral Web: combining social networks and collaborative filtering},
url = {http://doi.acm.org/10.1145/245108.245123},
volume = 40,
year = 1997
}
@inproceedings{derose2008building,
abstract = {The rapid growth of Web communities has motivated many solutions for building community data portals. These solutions follow roughly two approaches. The first approach (e.g., Libra, Citeseer, Cimple) employs semi-automatic methods to extract and integrate data from a multitude of data sources. The second approach (e.g., Wikipedia, Intellipedia) deploys an initial portal in wiki format, then invites community members to revise and add material. In this paper we consider combining the above two approaches to building community portals. The new hybrid machine-human approach brings significant benefits. It can achieve broader and deeper coverage, provide more incentives for users to contribute, and keep the portal more up-to-date with less user effort. In a sense, it enables building "community wikipedias", backed by an underlying structured database that is continuously updated using automatic techniques. We outline our ideas for the new approach, describe its challenges and opportunities, and provide initial solutions. Finally, we describe a real-world implementation and preliminary experiments that demonstrate the utility of the new approach.},
author = {DeRose, P. and Chai, Xiaoyong and Gao, B.J. and Shen, W. and Doan, An Hai and Bohannon, P. and Zhu, Xiaojin},
booktitle = {24th International Conference on Data Engineering},
doi = {10.1109/ICDE.2008.4497473},
interhash = {00f45357225b1e75ed93bddb8d456fb7},
intrahash = {38a2e84d3dfd845d9c260d5f15161c6f},
month = apr,
pages = {646--655},
publisher = {IEEE},
title = {Building Community Wikipedias: A Machine-Human Partnership Approach},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4497473&tag=1},
year = 2008
}
@inproceedings{chi2009augmented,
abstract = {We are experiencing a new Social Web, where people share, communicate, commiserate, and conflict with each other. As evidenced by systems like Wikipedia, twitter, and delicious.com, these environments are turning people into social information foragers and sharers. Groups interact to resolve conflicts and jointly make sense of topic areas from "Obama vs. Clinton" to "Islam." PARC's Augmented Social Cognition researchers -- who come from cognitive psychology, computer science, HCI, CSCW, and other disciplines -- focus on understanding how to "enhance a group of people's ability to remember, think, and reason". Through Social Web systems like social bookmarking sites, blogs, Wikis, and more, we can finally study, in detail, these types of enhancements on a very large scale.
Here we summarize recent work and early findings such as: (1) how conflict and coordination have played out in Wikipedia, and how social transparency might affect reader trust; (2) how decreasing interaction costs might change participation in social tagging systems; and (3) how computation can help organize user-generated content and metadata.},
acmid = {1559959},
address = {New York, NY, USA},
author = {Chi, Ed H.},
booktitle = {Proceedings of the 2009 ACM SIGMOD International Conference on Management of data},
doi = {10.1145/1559845.1559959},
interhash = {d24a64ce5e95bae4de9329a467342dee},
intrahash = {d09b484b1036ca8273743cac1992dd7f},
isbn = {978-1-60558-551-2},
location = {Providence, Rhode Island, USA},
numpages = {12},
pages = {973--984},
publisher = {ACM},
title = {Augmented social cognition: using social web technology to enhance the ability of groups to remember, think, and reason},
url = {http://doi.acm.org/10.1145/1559845.1559959},
year = 2009
}
@inproceedings{donato2010notes,
abstract = {Addressing user's information needs has been one of the main goals of Web search engines since their early days. In some cases, users cannot see their needs immediately answered by search results, simply because these needs are too complex and involve multiple aspects that are not covered by a single Web or search results page. This typically happens when users investigate a certain topic in domains such as education, travel or health, which often require collecting facts and information from many pages. We refer to this type of activities as "research missions". These research missions account for 10% of users' sessions and more than 25% of all query volume, as verified by a manual analysis that was conducted by Yahoo! editors.
We demonstrate in this paper that such missions can be automatically identified on-the-fly, as the user interacts with the search engine, through careful runtime analysis of query flows and query sessions.
The on-the-fly automatic identification of research missions has been implemented in Search Pad, a novel Yahoo! application that was launched in 2009, and that we present in this paper. Search Pad helps users keeping trace of results they have consulted. Its novelty however is that unlike previous notes taking products, it is automatically triggered only when the system decides, with a fair level of confidence, that the user is undertaking a research mission and thus is in the right context for gathering notes. Beyond the Search Pad specific application, we believe that changing the level of granularity of query modeling, from an isolated query to a list of queries pertaining to the same research missions, so as to better reflect a certain type of information needs, can be beneficial in a number of other Web search applications. Session-awareness is growing and it is likely to play, in the near future, a fundamental role in many on-line tasks: this paper presents a first step on this path.},
acmid = {1772724},
address = {New York, NY, USA},
author = {Donato, Debora and Bonchi, Francesco and Chi, Tom and Maarek, Yoelle},
booktitle = {Proceedings of the 19th international conference on World wide web},
doi = {10.1145/1772690.1772724},
interhash = {3f9d8d91da75a41a35f8ba521beb559d},
intrahash = {2e2c2c1d1b7fcd30f11cbde5729f554e},
isbn = {978-1-60558-799-8},
location = {Raleigh, North Carolina, USA},
numpages = {10},
pages = {321--330},
publisher = {ACM},
title = {Do you want to take notes?: identifying research missions in Yahoo! search pad},
url = {http://doi.acm.org/10.1145/1772690.1772724},
year = 2010
}
@article{chen2007reputation,
abstract = {In this paper, we propose a user reputation model and apply it to a user-interactive question answering system. It combines the social network analysis approach and the user rating approach. Social network analysis is applied to analyze the impact of participant users' relations to their reputations. User rating is used to acquire direct judgment of a user's reputation based on other users' experiences with this user. Preliminary experiments show that the computed reputations based on our proposed reputation model can reflect the actual reputations of the simulated roles and therefore can fit in well with our user-interactive question answering system. Copyright © 2006 John Wiley & Sons, Ltd.},
author = {Chen, Wei and Zeng, Qingtian and Wenyin, Liu and Hao, Tianyong},
doi = {10.1002/cpe.1142},
interhash = {c304f655ee6ee183e07192b9fed0d618},
intrahash = {858df3646b706ce6308a12cbf1585d58},
issn = {1532-0634},
journal = {Concurrency and Computation: Practice and Experience},
number = 15,
pages = {2091--2103},
publisher = {John Wiley & Sons, Ltd.},
title = {A user reputation model for a user-interactive question answering system},
url = {http://dx.doi.org/10.1002/cpe.1142},
volume = 19,
year = 2007
}
@incollection{yu2000social,
abstract = {Trust is important wherever agents must interact. We consider the important case of interactions in electronic communities, where the agents assist and represent principal entities, such as people and businesses. We propose a social mechanism of reputation management, which aims at avoiding interaction with undesirable participants. Social mechanisms complement hard security techniques (such as passwords and digital certificates), which only guarantee that a party is authenticated and authorized, but do not ensure that it exercises its authorization in a way that is desirable to others. Social mechanisms are even more important when trusted third parties are not available. Our specific approach to reputation management leads to a decentralized society in which agents help each other weed out undesirable players.},
address = {Berlin/Heidelberg},
affiliation = {Department of Computer Science, North Carolina State University, Raleigh, NC 27695-7534, USA},
author = {Yu, Bin and Singh, Munindar},
booktitle = {Cooperative Information Agents IV - The Future of Information Agents in Cyberspace},
doi = {10.1007/978-3-540-45012-2_15},
editor = {Klusch, Matthias and Kerschberg, Larry},
interhash = {1065a4963600ef4f9b4c034d3bbd9a50},
intrahash = {337afcb67138b927b27a9687199e8568},
isbn = {978-3-540-67703-1},
keyword = {Computer Science},
pages = {355--393},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {A Social Mechanism of Reputation Management in Electronic Communities},
url = {http://dx.doi.org/10.1007/978-3-540-45012-2_15},
volume = 1860,
year = 2000
}
@inproceedings{yu2003searching,
abstract = {A referral system is a multiagent system whose member agents are capable of giving and following referrals. The specific cases of interest arise where each agent has a user. The agents cooperate by giving and taking referrals so each can better help its user locate relevant information. This use of referrals mimics human interactions and can potentially lead to greater effectiveness and efficiency than in single-agent systems.Existing approaches consider what referrals may be given and treat the referring process simply as path search in a static graph. By contrast, the present approach understands referrals as arising in and influencing dynamic social networks, where the agents act autonomously based on local knowledge. This paper studies strategies using which agents may search dynamic social networks. It evaluates the proposed approach empirically for a community of AI scientists (partially derived from bibliographic data). Further, it presents a prototype system that assists users in finding other users in practical social networks.},
acmid = {860587},
address = {New York, NY, USA},
author = {Yu, Bin and Singh, Munindar P.},
booktitle = {Proceedings of the second international joint conference on Autonomous agents and multiagent systems},
doi = {10.1145/860575.860587},
interhash = {1d5f1932e29ea02f82948d4efd12a0ad},
intrahash = {c6b422948459e04a86e766055608e55e},
isbn = {1-58113-683-8},
location = {Melbourne, Australia},
numpages = {8},
pages = {65--72},
publisher = {ACM},
title = {Searching social networks},
url = {http://doi.acm.org/10.1145/860575.860587},
year = 2003
}
@inproceedings{jurczyk2007discovering,
abstract = {Question-Answer portals such as Naver and Yahoo! Answers are quickly becoming rich sources of knowledge on many topics which are not well served by general web search engines. Unfortunately, the quality of the submitted answers is uneven, ranging from excellent detailed answers to snappy and insulting remarks or even advertisements for commercial content. Furthermore, user feedback for many topics is sparse, and can be insufficient to reliably identify good answers from the bad ones. Hence, estimating the authority of users is a crucial task for this emerging domain, with potential applications to answer ranking, spam detection, and incentive mechanism design. We present an analysis of the link structure of a general-purpose question answering community to discover authoritative users, and promising experimental results over a dataset of more than 3 million answers from a popular community QA site. We also describe structural differences between question topics that correlate with the success of link analysis for authority discovery.},
acmid = {1321575},
address = {New York, NY, USA},
author = {Jurczyk, Pawel and Agichtein, Eugene},
booktitle = {Proceedings of the sixteenth ACM conference on Conference on information and knowledge management},
doi = {10.1145/1321440.1321575},
interhash = {1c2953be3517384681b6ac831da2c766},
intrahash = {35394620d2654db8543d5da60f6f00dc},
isbn = {978-1-59593-803-9},
location = {Lisbon, Portugal},
numpages = {4},
pages = {919--922},
publisher = {ACM},
title = {Discovering authorities in question answer communities by using link analysis},
url = {http://doi.acm.org/10.1145/1321440.1321575},
year = 2007
}
@inproceedings{agichtein2008finding,
abstract = {The quality of user-generated content varies drastically from excellent to abuse and spam. As the availability of such content increases, the task of identifying high-quality content sites based on user contributions --social media sites -- becomes increasingly important. Social media in general exhibit a rich variety of information sources: in addition to the content itself, there is a wide array of non-content information available, such as links between items and explicit quality ratings from members of the community. In this paper we investigate methods for exploiting such community feedback to automatically identify high quality content. As a test case, we focus on Yahoo! Answers, a large community question/answering portal that is particularly rich in the amount and types of content and social interactions available in it. We introduce a general classification framework for combining the evidence from different sources of information, that can be tuned automatically for a given social media type and quality definition. In particular, for the community question/answering domain, we show that our system is able to separate high-quality items from the rest with an accuracy close to that of humans},
acmid = {1341557},
address = {New York, NY, USA},
author = {Agichtein, Eugene and Castillo, Carlos and Donato, Debora and Gionis, Aristides and Mishne, Gilad},
booktitle = {Proceedings of the international conference on Web search and web data mining},
doi = {10.1145/1341531.1341557},
interhash = {72c7bf5d1c983c47bfc3c6cc9084c26c},
intrahash = {29c5c74d95dce215a9692b94fc619839},
isbn = {978-1-59593-927-2},
location = {Palo Alto, California, USA},
numpages = {12},
pages = {183--194},
publisher = {ACM},
title = {Finding high-quality content in social media},
url = {http://doi.acm.org/10.1145/1341531.1341557},
year = 2008
}