Social search

Definition and Overview of Social Search - Social search is a behavior of retrieving and searching on a social searching engine that mainly searches user-generated content such as news, videos, and images related to search queries on social media platforms. - It combines traditional algorithms with the idea of taking into account social relationships between search results and the searcher. - Social search is a personalized search technology that uses online community filtering to produce highly personalized results. - It aims to provide more meaningful and relevant results by leveraging human network-oriented results instead of relying solely on computer algorithms. - Social search can be performed on various platforms such as search engines, social media platforms, and specialized social search engines. - It utilizes social signals such as likes, shares, and comments to influence search rankings. - The goal of social search is to enhance the search experience by leveraging social interactions and recommendations. Benefits and Limitations of Social Search - Social search is not demonstrably better than algorithm-driven search. - It highlights content that was created or touched by other users in the social graph of the person conducting the search. - It allows for a shared and rich search experience through recommendations generated based on search results. - It can improve the relevance of results for future searches of a particular keyword. - It provides a more personalized search experience by considering social relationships and connections. - Privacy concerns arise when personal information is used for social search. - The reliability and credibility of user-generated content can be a challenge in social search. - The diversity of social networks and preferences can make it difficult to provide personalized search results. - Social search algorithms need to constantly adapt to changing social dynamics and user behavior. - The balance between personalized search results and maintaining diversity in search results is a challenge. Research and Implementations of Social Search - Various startup companies focused on ranking search results according to one's social graph on social networks. - Companies in the social search space include Evam-SOCOTO Wajam, Slangwho, Sproose, Mahalo, Jumper 2.0, Qitera, Scour, Wink, Eurekster, Baynote, Delver, and OneRiot. - Google introduced Social Search in 2009, which was later expanded to multiple languages. - Bing and Google started considering re-tweets and Likes when providing search results. - HeyStaks developed a web browser plugin that applies social search through collaboration in web search to improve search results. Social Discovery - Social discovery uses social preferences and personal information to predict desirable content for users. - It enables the discovery of new people, experiences, shopping, and traveling. - Real-time social discovery is facilitated by mobile apps. - Social discovery contributes to sales and revenue for companies through social media. - Facebook's profitability is based on social discovery, generating ad revenue by targeting ads to users using their social connections. Social Search Engines - A social search engine provides answers to questions by identifying a person in the answer. - It retrieves user-submitted queries related to the question and provides an answer with a link to the resource. - Social search engines leverage user-generated content and social connections to enhance search results. - They can be used to discover new people, experiences, and products. - Social search engines contribute to the profitability of platforms like Facebook by targeting ads based on social connections.