# Scalable Knowledge Graph Construction from Twitter

## TL;DR

This paper presents a scalable method for constructing a knowledge graph from Twitter data, focusing on filtering noise and enabling diverse relationship queries for innovative applications.

## Contribution

It introduces a novel approach to build a high-quality, scalable knowledge graph from noisy social media data, facilitating complex relationship discovery.

## Key findings

- Successfully filters noise from Twitter data
- Enables multi-angle querying of relationships
- Supports development of new social media applications

## Abstract

We describe a knowledge graph derived from Twitter data with the goal of discovering relationships between people, links, and topics. The goal is to filter out noise from Twitter and surface an inside-out view that relies on high quality content. The generated graph contains many relationships where the user can query and traverse the structure from different angles allowing the development of new applications.