Search Results - "2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining"

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  1. 1

    Studying User Footprints in Different Online Social Networks by Malhotra, A., Totti, L., Meira, W., Kumaraguru, P., Almeida, V.

    “…With the growing popularity and usage of online social media services, people now have accounts (some times several) on multiple and diverse services like…”
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    Conference Proceeding
  2. 2

    On Learning Cluster Coefficient of Private Networks by Wang, Yue, Wu, Xintao, Zhu, Jun, Xiang, Yang

    Published in Social network analysis and mining (01-01-2012)
    “…Enabling accurate analysis of social network data while preserving differential privacy has been challenging since graph features such as clustering…”
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    Conference Proceeding Journal Article
  3. 3

    Sentiment Analysis on Social Media by Neri, F., Aliprandi, C., Capeci, F., Cuadros, M., By, T.

    “…The Web is a huge virtual space where to express and share individual opinions, influencing any aspect of life, with implications for marketing and…”
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    Conference Proceeding
  4. 4

    Communities and Balance in Signed Networks: A Spectral Approach by Anchuri, P., Magdon-Ismail, M.

    “…Discussion based websites like Epinions.com and Slashdot.com allow users to identify both friends and foes. Such networks are called Signed Social Networks and…”
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    Conference Proceeding
  5. 5

    Predicting Personality with Social Behavior by Adali, S., Golbeck, J.

    “…In this paper, we examine to which degree behavioral measures can be used to predict personality. Personality is one factor that dictates people's propensity…”
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    Conference Proceeding
  6. 6

    Using Pregel-like Large Scale Graph Processing Frameworks for Social Network Analysis by Quick, L., Wilkinson, P., Hardcastle, D.

    “…Pregel is a system for large scale graph processing developed at Google. It provides a scalable framework for running graph analytics on clusters of commodity…”
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    Conference Proceeding
  7. 7

    A Guide to Differential Privacy Theory in Social Network Analysis by Task, C., Clifton, C.

    “…Privacy of social network data is a growing concern which threatens to limit access to this valuable data source. Analysis of the graph structure of social…”
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    Conference Proceeding
  8. 8

    Analyzing User Retweet Behavior on Twitter by Zhiheng Xu, Qing Yang

    “…This paper provides a deep analysis of user retweet behavior on Twitter. While previous works about analyzing retweet have mainly focused on predicting the…”
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    Conference Proceeding
  9. 9

    Link Prediction: Fair and Effective Evaluation by Lichtnwalter, R., Chawla, N. V.

    “…Link prediction is a popular area for publication. Papers appear in virtually every conference on data mining or network science with new methods. We argue…”
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    Conference Proceeding
  10. 10

    Combining Relations and Text in Scientific Network Clustering by Combe, D., Largeron, C., Egyed-Zsigmond, E., Gery, M.

    “…In this paper, we present different combined clustering methods and we evaluate their performances and their results on a dataset with ground truth. This…”
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    Conference Proceeding
  11. 11

    Twitter as a Tool for Predicting Elections Results by Soler, J. M., Cuartero, F., Roblizo, M.

    “…The use of social networking sites, such as Twitter, for various purposes, continues to grown since its first appearance. This social net is a microblogging…”
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    Conference Proceeding
  12. 12

    FakeBook: Detecting Fake Profiles in On-Line Social Networks by Conti, M., Poovendran, R., Secchiero, M.

    “…On-line Social Networks (OSNs) are increasingly influencing the way people communicate with each other and share personal, professional and political…”
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    Conference Proceeding
  13. 13

    Semantic Expansion of Tweet Contents for Enhanced Event Detection in Twitter by Ozdikis, O., Senkul, P., Oguztuzun, H.

    “…This paper aims to enhance event detection methods in a micro-blogging platform, namely Twitter. The enhancement technique we propose is based on…”
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    Conference Proceeding
  14. 14

    A Method for Local Community Detection by Finding Core Nodes by Tiantian Zhang, Bin Wu

    “…Currently, the detection of global community structure in networks has gathered a lot of attention. Most of the methods need global knowledge of the graphs…”
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    Conference Proceeding
  15. 15

    Diffusion Centrality in Social Networks by Chanhyun Kang, Molinaro, C., Kraus, S., Shavitt, Y., Subrahmanian, V. S.

    “…Though centrality of vertices in social networks has been extensively studied, all past efforts assume that centrality of a vertex solely depends on the…”
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    Conference Proceeding
  16. 16

    Fast Exact Computation of betweenness Centrality in Social Networks by Baglioni, M., Geraci, F., Pellegrini, M., Lastres, E.

    “…Social networks have demonstrated in the last few years to be a powerful and flexible concept useful to represent and analyze data emerging form social…”
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    Conference Proceeding
  17. 17

    Identification of Group Changes in Blogosphere by Gliwa, B., Saganowski, S., Zygmunt, A., Brodka, P., Kazienko, P., Kozak, J.

    “…The paper addresses a problem of change identification in social group evolution. A new SGCI method for discovering of stable groups was proposed and compared…”
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    Conference Proceeding
  18. 18

    A Complex Network Analysis of the United States Air Transportation by Cheung, D. P., Gunes, M. H.

    “…The air transportation industry has a great impact on the economy. In this paper, we analyze the air transportation network in the U.S. to better understand…”
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    Conference Proceeding
  19. 19

    Large Social Networks Can Be Targeted for Viral Marketing with Small Seed Sets by Shakarian, P., Paulo, D.

    “…In a "tipping" model, each node in a social network, representing an individual, adopts a behavior if a certain number of his incoming neighbors previously…”
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    Conference Proceeding
  20. 20

    Percolation Computation in Complex Networks by Reid, F., McDaid, A., Hurley, N.

    “…K-clique percolation is an overlapping community finding algorithm which extracts particular structures, comprised of overlapping cliques, from complex…”
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    Conference Proceeding