RESEARCH PAPER ON  CORRELATION MaxQDPro Team Anjan.K Harish.R II Sem M.Tech CSE 06/10/09 Research Paper On Corelation
Prerequisites Introduction  Paper Key Terminologies Abstract Contributions Characterizing the Social Network Surfing the paper  Future Work Conclusion References AGENDA 06/10/09 Research Paper On Corelation
Data Mining Concepts Key Concepts Co-relation analysis Social Networks Instant Messaging or any Chat application Social and Behavioral Sciences Demographics Fair Knowledge of issues in Cyber World Enough Moral and emotional maturity to understand it. PREREQUISITES 06/10/09 Research Paper On Corelation
A MACROSCOPIC FOCUS ON THE PAPER  06/10/09 Research Paper On Corelation “YES, THERE IS CORRELATION FROM SOCIAL NETWORKS TO PERSONAL BEHAVIOR ON THE WEB”
INTRODUCTION – PAPER  (1) Authors  –  Parag Singla of University of Washington, Seattle, USA Matthew Richardson, Microsoft R&D, Redmond,USA Paper  was first presented at International World Wide web Conference Committee(IW3C2) . Study and survey started from 2005 and later Permission to use the paper to classroom and personal reference use only. Key words Social and Behavioral Sciences Social Networks Instant Messaging Demographics ACM Transaction on Knowledge Discovery Process ,April  2008. 06/10/09 Research Paper On Corelation
INTRODUCTION-KEY TERMINOLOGIES (2) Behavioral Sciences A study of determining the behavior of a person or people in society Social Network  Social Structure made of nodes that are tied by one or more specific types of interdependency, such as values, visions, ideas, financial exchange, friendship, sexual relationship, kinship Social network analysis views social relationship in terms of  nodes  and  ties .  Demographics refers to selected population characteristics as used in government, marketing or opinion research, or the demographic profiles used in such research.  Commonly-used demographics include race, age, income, disabilities, mobility (in terms of travel time to work or number of vehicles available), educational attainment, home ownership, employment status, and even location.  The idea that people with similar characteristics tend to be connected is called homophily. 06/10/09 Research Paper On Corelation
INTRODUCTION-ABSTRACT (3) Characterizing the relationship that exists between a person’s social group and his/her personal behavior has been a long standing goal of social network analysts.  In this paper, we apply data mining techniques to study this relationship for a population of over 10 million people, by turning to online sources of data.  The analysis reveals that people who chat with each other (using instant messaging) are more likely to share interests (their Web searches are the same or topically similar).  The more time they spend talking, the stronger this relationship is. People who chat with each other are also more likely to share other personal characteristics, such as their age and location (and, they are likely to be of opposite gender). Similar findings hold for people who do not necessarily talk to each other but do have a friend in common.  Our analysis is based on a well-defined mathematical formulation of the problem 06/10/09 Research Paper On Corelation
Given that two people are connected over the Internet, paper answer some of the question of eager curiosity  Are they similar to each other? How does their connection affect their personal behavior?  How does their behavior vary based on the type of connection? Its finds its application in detecting Cyber Crime since there is lot of stress Cyber Confidentiality. Also helps parents to understand behavior of their wards and to protect them against vulgarity. INTRODUCTION – CONTRIBUTIONS (4) 06/10/09 Research Paper On Corelation
CHARACTERIZING THE SOCIAL NETWORK Search Engines are personalized Intelligent Chat like recommending a friend to join a network or use an application Analyze the relation between communication and personal behavior, we need two sources of data: (1) Who communicates with whom, and  (2) The characteristics of each person in the  communication network. Demographic parameters are person’s age, gender and geographical location Correlation hold on the metrics used. 06/10/09 Research Paper On Corelation
SURFING THE PAPER Correlation is made on the basis of the time duration spent by person in the chat conversation. Classification is done by Bayesian Classifier Datasets assumed are Social Network Data Personal Interests Data Joining Data Experiments Computing the similarities Establishing the correlation Varying talk time. Condition on the Personal attribute Effects of the Indirect links 06/10/09 Research Paper On Corelation
RELATED WORK McPherson etal. give an excellent review of work done on homophily in real-world networks. Sproull and Patterson discuss how the participation in online communities might affect the every day lives and behavior of the people in the physical world. Handcock and Raftery’s model for social networks incorporates assumptions about transitivity in link structure. "Web homophily" can be used to advantage in, for example, finding communities of Web pages and the ranking of Web pages. 06/10/09 Research Paper On Corelation
Search similarity and IM talk time extend to the case of whether users click on advertisements as well. To build a more predictive model for both. Experiment on multi-user chat sessions, see proposed model of correlations is valid. Query behavior of the users through time, to discover what types of queries tend to spread through the network, and what other queries do not. Finally, examine whether the correlations discovered here are found in other domains, such as online gaming environments and social networking sites FUTURE WORK 06/10/09 Research Paper On Corelation
Users who talk to each other in an IM environment are significantly more likely to share interests than a random pair of users. Probabilistic model over users and their attributes and relations. The similarity between users strengthens with the amount of time they spend talking to each other. First experimental study of its kind and demonstrate significant promise for further research in this area, paving the way for many advances CONCLUSION 06/10/09 Research Paper On Corelation
[1] A. Abbott, editor.  The American Journal of Sociology, 2006. [2] P. Bearman, J. Moody, and K. Stovel. Chains of affection:the structure of adolescent romantic and sexual networks. American Journal of Sociology, 110:44–91, 2004. [3] A. Broder. A taxonomy of web search. In  25th Intl. SIGIR, pages 3–10, 2002. [4] S. Chien and N. Immorlica. Semantic similarity betweensearch engine queries using temporal correlation. In  14 th   Intl. WWW, pages 2–11, 2005. [5] P. Domingos and M. Pazzani. On the optimality of the simple Bayesian classifier under zero-one loss.  Machine Learning,  29:103–130, 1997. REFERENCES 06/10/09 Research Paper On Corelation
PROPAGATE GOOD THING TO OTHER Duty as responsible engineers towards protection of  Environment “ Ecological Footprint” Mother Earth  Please Visit    http://  www.lightchannels.com Grow or Plant a tree and give it a name  they are living being as well. 06/10/09 Research Paper On Corelation
THANK YOU 06/10/09 Research Paper On Corelation

Research Paper On Correlation

  • 1.
    RESEARCH PAPER ON CORRELATION MaxQDPro Team Anjan.K Harish.R II Sem M.Tech CSE 06/10/09 Research Paper On Corelation
  • 2.
    Prerequisites Introduction Paper Key Terminologies Abstract Contributions Characterizing the Social Network Surfing the paper Future Work Conclusion References AGENDA 06/10/09 Research Paper On Corelation
  • 3.
    Data Mining ConceptsKey Concepts Co-relation analysis Social Networks Instant Messaging or any Chat application Social and Behavioral Sciences Demographics Fair Knowledge of issues in Cyber World Enough Moral and emotional maturity to understand it. PREREQUISITES 06/10/09 Research Paper On Corelation
  • 4.
    A MACROSCOPIC FOCUSON THE PAPER 06/10/09 Research Paper On Corelation “YES, THERE IS CORRELATION FROM SOCIAL NETWORKS TO PERSONAL BEHAVIOR ON THE WEB”
  • 5.
    INTRODUCTION – PAPER (1) Authors – Parag Singla of University of Washington, Seattle, USA Matthew Richardson, Microsoft R&D, Redmond,USA Paper was first presented at International World Wide web Conference Committee(IW3C2) . Study and survey started from 2005 and later Permission to use the paper to classroom and personal reference use only. Key words Social and Behavioral Sciences Social Networks Instant Messaging Demographics ACM Transaction on Knowledge Discovery Process ,April 2008. 06/10/09 Research Paper On Corelation
  • 6.
    INTRODUCTION-KEY TERMINOLOGIES (2)Behavioral Sciences A study of determining the behavior of a person or people in society Social Network Social Structure made of nodes that are tied by one or more specific types of interdependency, such as values, visions, ideas, financial exchange, friendship, sexual relationship, kinship Social network analysis views social relationship in terms of  nodes  and  ties . Demographics refers to selected population characteristics as used in government, marketing or opinion research, or the demographic profiles used in such research. Commonly-used demographics include race, age, income, disabilities, mobility (in terms of travel time to work or number of vehicles available), educational attainment, home ownership, employment status, and even location. The idea that people with similar characteristics tend to be connected is called homophily. 06/10/09 Research Paper On Corelation
  • 7.
    INTRODUCTION-ABSTRACT (3) Characterizingthe relationship that exists between a person’s social group and his/her personal behavior has been a long standing goal of social network analysts. In this paper, we apply data mining techniques to study this relationship for a population of over 10 million people, by turning to online sources of data. The analysis reveals that people who chat with each other (using instant messaging) are more likely to share interests (their Web searches are the same or topically similar). The more time they spend talking, the stronger this relationship is. People who chat with each other are also more likely to share other personal characteristics, such as their age and location (and, they are likely to be of opposite gender). Similar findings hold for people who do not necessarily talk to each other but do have a friend in common. Our analysis is based on a well-defined mathematical formulation of the problem 06/10/09 Research Paper On Corelation
  • 8.
    Given that twopeople are connected over the Internet, paper answer some of the question of eager curiosity Are they similar to each other? How does their connection affect their personal behavior? How does their behavior vary based on the type of connection? Its finds its application in detecting Cyber Crime since there is lot of stress Cyber Confidentiality. Also helps parents to understand behavior of their wards and to protect them against vulgarity. INTRODUCTION – CONTRIBUTIONS (4) 06/10/09 Research Paper On Corelation
  • 9.
    CHARACTERIZING THE SOCIALNETWORK Search Engines are personalized Intelligent Chat like recommending a friend to join a network or use an application Analyze the relation between communication and personal behavior, we need two sources of data: (1) Who communicates with whom, and (2) The characteristics of each person in the communication network. Demographic parameters are person’s age, gender and geographical location Correlation hold on the metrics used. 06/10/09 Research Paper On Corelation
  • 10.
    SURFING THE PAPERCorrelation is made on the basis of the time duration spent by person in the chat conversation. Classification is done by Bayesian Classifier Datasets assumed are Social Network Data Personal Interests Data Joining Data Experiments Computing the similarities Establishing the correlation Varying talk time. Condition on the Personal attribute Effects of the Indirect links 06/10/09 Research Paper On Corelation
  • 11.
    RELATED WORK McPhersonetal. give an excellent review of work done on homophily in real-world networks. Sproull and Patterson discuss how the participation in online communities might affect the every day lives and behavior of the people in the physical world. Handcock and Raftery’s model for social networks incorporates assumptions about transitivity in link structure. "Web homophily" can be used to advantage in, for example, finding communities of Web pages and the ranking of Web pages. 06/10/09 Research Paper On Corelation
  • 12.
    Search similarity andIM talk time extend to the case of whether users click on advertisements as well. To build a more predictive model for both. Experiment on multi-user chat sessions, see proposed model of correlations is valid. Query behavior of the users through time, to discover what types of queries tend to spread through the network, and what other queries do not. Finally, examine whether the correlations discovered here are found in other domains, such as online gaming environments and social networking sites FUTURE WORK 06/10/09 Research Paper On Corelation
  • 13.
    Users who talkto each other in an IM environment are significantly more likely to share interests than a random pair of users. Probabilistic model over users and their attributes and relations. The similarity between users strengthens with the amount of time they spend talking to each other. First experimental study of its kind and demonstrate significant promise for further research in this area, paving the way for many advances CONCLUSION 06/10/09 Research Paper On Corelation
  • 14.
    [1] A. Abbott,editor. The American Journal of Sociology, 2006. [2] P. Bearman, J. Moody, and K. Stovel. Chains of affection:the structure of adolescent romantic and sexual networks. American Journal of Sociology, 110:44–91, 2004. [3] A. Broder. A taxonomy of web search. In 25th Intl. SIGIR, pages 3–10, 2002. [4] S. Chien and N. Immorlica. Semantic similarity betweensearch engine queries using temporal correlation. In 14 th Intl. WWW, pages 2–11, 2005. [5] P. Domingos and M. Pazzani. On the optimality of the simple Bayesian classifier under zero-one loss. Machine Learning, 29:103–130, 1997. REFERENCES 06/10/09 Research Paper On Corelation
  • 15.
    PROPAGATE GOOD THINGTO OTHER Duty as responsible engineers towards protection of Environment “ Ecological Footprint” Mother Earth Please Visit http:// www.lightchannels.com Grow or Plant a tree and give it a name they are living being as well. 06/10/09 Research Paper On Corelation
  • 16.
    THANK YOU 06/10/09Research Paper On Corelation