Data Science in Social Media

1. Data Science in Social Media Naveen Kumar Sridhar

2. Data Reliability • Trust • Relation between Reliability and Trust • Ontologies • SPARQL • Future work Agenda

3. One of my friends posted a status message on Facebook, No classes today. Thank you Irene. First question that came to my mind, Is this person reliable? Motivation

4. Definition: Reliable data is evidence you can trust. Example: If two people are doing the experiment and the result is almost same most of the time, then we consider the data to be reliable. In social network like Facebook, data can be classified as reliable data based on the trust on a person who posts the data. Data Reliability

5. Definition ‘Evidence’ is data which is judged to be relevant. Example: When you investigate cooling, temperature data is relevant, so it is evidence. The length of the thermometer is not relevant, so it is not evidence. Evidence

6. Definition: Trust in a person is a commitment to an action based on a belief that the future actions of that person will lead to good outcome. (Golbeck and Hendler) Example: A believes in B expecting that B provides certain information which are correct to the context. Trust

7. Direct Trust • Relational Trust • System Trust Trust Types

8. Scenarios: • You know a mechanic who has already repaired your car. • You know a friend who lives in Chennai. He posts a status message Weather is pretty cool Do not forget that trust is contextual Direct Trust

9. Scenarios • You are new to Troy. You have to buy some apples. Your friend says ‘Price Chopper is the right place’ • Your friend likes a status message of his friend in Facebook ‘There is a DJ tonite @ Brown’s’ Relational Trust

10. Scenarios • You are going to a small town which has a small grocery store. They have only nameless toothpaste. You can see a FDA approval over the label. • You see a message posted by some person you don’t know. You can see that he is from RPI or Stanford. System Trust

11. Facebook Data

12. Definition An ontology is an explicit specification of a conceptualization Tools: Protégé 4.2.0 Link: https://dl-web.dropbox.com/get/Independent%20Study/OntologyTrustFacebook.owl?w=3db9b219 Ontology

13. SPARQL stands for SPARQL Protocol and RDF Query Language. • Used SPARQL to query the data obtained from Facebook which was in the RDF form. • This can be integrated later with the ontology so that we can infer trust values directly. SPARQL

14. Trustor is someone who must choose whether, and how much, to trust. • Trustee is someone or something that is to be trusted • The ontology is designed to find the different forms of trusted Trustees. Ontology Explanation

15. Trustee class is divided into five sub-classes • Completely Trusted • Somewhat Trusted • Somewhat Untrusted • Completely Untrusted • Don’t know Ontology Explanation

16. Trust classes are • Association – To find out whether there is an association between trustor and trustee • PriorKnowledge – To find out whether the trustee has prior knowledge • Metadata Source – To find out whether Trustee has valid IP address • SourceOfData – To find out whether trustee has mentioned the links of the source Ontology Explanation

17. Completely Trusted – Trustee is a professor/has a professional relationship and has provided the source link of data and has prior knowledge. • Somewhat Trusted – Trustee is a professor/ has a professional relationship/has provided the source and also has prior knowledge • Somewhat Untrusted – Trustee is not having any one these:priorknowledge/link/association Ontology Explanation

18. Completely Untrusted – Trustee has no trust factors associated with him • Don’t know – If the trustee does not fall in any of the four categories mentioned above categories. Ontology Explanation

19. Sample RDF is placed in an existing triple store • As data is sensitive, I pulled data for one person(any amount of data is possible) • Data in Facebook which I can see when I am online, is pulled from graph API in RDF format. Link : http://bit.ly/t67iav SPARQL End Point

20. Ontology will be used to infer trust of the data from Facebook(complete model) • PML Trust Ontology can be created for Social Networks. Future Work

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