Social Search

Anantaa Kotal ([email protected]) Why use Social Search?

• Naïve Information Retrieval – Assumes Individual Search is solitary – Does not account for social context • Social Network help us understand context for a query What is Social Search?

• Social Search – Tries to improve results by understanding the social context – Uses Social Network to bind the search space and improve ranking – Provides a personalized and targeted approach for IR Searching over Social data

• Web 2.0 entities: – Like documents, persons, tags etc. – Heterogenous objects – Related by a Concept • Extend search space to objects with similar concept – “Social search and discovery using a unified approach” [1] Personalized Searching

• User Profile: – Contains information about User – Includes peers connected to User • Using implict and explicit information provided in the User profile to augment search results – “Personalized expertise search at LinkedIn" [2] Social Network • Can be thought of as a graph – Users are nodes – Users have attributes – Edges are user connections • Objective is to find group of users that can influence individual information needs Familiarity

• Do they know each other? Employee 1 Employee 2 • Direct Familiarity: Connected in any of the social network domains • Indirect Familiarity: Have common mutual connections Manager Similarity

• Users that have: – Similar activity – Similar user profile • Identifies: Doc Doc – usage of the same tag 1 2 – tagging of the same document – membership of the same community – commenting on the same blog entry

Query 1 Query 2 Social Search in Popular Websites

• Personalized social search based on the user’s social network.[3] – Investigates Familiarity vs Similarity in Social Search • An elaborated model of social search [4] – suggests where in the search process shared information may be valuable to individual searchers • Personalized expertise search at LinkedIn [2] – Uses LinkedIn user profile to filter search results • Personalized News and Blog Recommendations based on User Location, Facebook and Twitter User Profiling [5] – personalizes the search matrix for an user by leveraging and combining the user's location, their Facebook and/or Twitter feed Challenges

SECURITY PRIVACY ETHICAL DATA SHARING References

1. Amitay, Einat, et al. “Social search and discovery using a unified approach.” Proceedings of the 20th ACM Conference on Hypertext and Hypermedia. 2009 2. Ha-Thuc, Viet, et al. “Personalized expertise search at LinkedIn.” 2015IEEE International Conference on Big Data (Big Data). IEEE, 2015 3. Carmel, David, et al. “Personalized social search based on the user’s social network.” Proceedings of the 18th ACM conference on Information and knowledge management. 2009. 4. Evans, Brynn M., and Ed H. Chi. “An elaborated model of social search.” Information Processing & Management 46.6 (2010): 656-678. 5. Kazai, Gabriella, Iskander Yusof, and Daoud Clarke. “Personalised news and blog recommendations based on user location, Facebook and Twitter user profiling.” Proceedings of the 39th International ACM SI-GIR conference on Research and Development in Information Retrieval.2016