Student Research Day Abstracts and Posters

Title

Social Link

Document Type

Article

Publication Date

Fall 12-6-2017

Faculty Advisor(s)

Dr. Michael Fahy

Abstract

Employers often trawl applicants’ social media presences for objectionable behavior. We are creating a business facing application that streamlines the process, combining API data from LinkedIn with that of Twitter and cross referencing them. The difficulty comes down in aligning user profiles with different sets of attributes. For example, given an arbitrary applicant the LinkedIn API might give current city, university, and work history but Twitter might just have the current city. Being able to match these values and pinpoint specific profiles will take some time and a finely tuned algorithm. The final product will have a web-based UI that displays the search results using python to make the API calls and process the data. Relevant research includes the field of information retrieval.

Comments

Presented at the Fall 2017 Student Research Day at Chapman University.

Github URL: https://github.com/dd238/SocialLink

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