Using social network graph analysis for interest detection

TL;DR

This paper proposes using social network graph analysis as a robust proxy to better understand individuals' deeper interests and passions, overcoming limitations of traditional shallow interest models.

Contribution

It introduces a novel interest detection method based on social graph analysis, emphasizing the social graph's ability to reflect deeper personal interests.

Findings

Social graphs effectively represent deeper interests.

Traditional interest models capture only shallow, temporary interests.

Social graph analysis provides a more robust interest detection approach.

Abstract

A person's interests exist as an internal state and are difficult to define. Since only external actions are observable, a proxy must be used that represents someone's interests. Techniques like collaborative filtering, behavioral targeting, and hashtag analysis implicitly model an individual's interests. I argue that these models are limited to shallow, temporary interests, which do not reflect people's deeper interests or passions. I propose an alternative model of interests that takes advantage of a user's social graph. The basic principle is that people only follow those that interest them, so the social graph is an effective and robust proxy for people's interests.