# Mining Social Media for Open Innovation in Transportation Systems

arXiv: https://arxiv.org/abs/1610.09894 · HTML: https://mlsanity.com/paper/1610.09894/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Oct 2016.

## Built on by (most cited first, 1 of 1)

- [Leveraging Twitter Data for Sentiment Analysis of Transit User Feedback: An NLP Framework](https://mlsanity.com/paper/2310.07086/) (2023)

## Abstract (arXiv)

This work proposes a novel framework for the development of new products and services in transportation through an open innovation approach based on automatic content analysis of social media data. The framework is able to extract users comments from Online Social Networks (OSN), to process and analyze text through information extraction and sentiment analysis techniques to obtain relevant information about product reception on the market. A use case was developed using the mobile application Uber, which is today one of the fastest growing technology companies in the world. We measured how a controversial, highly diffused event influences the volume of tweets about Uber and the perception of its users. While there is no change in the image of Uber, a large increase in the number of tweets mentioning the company is observed, which meant a free and important diffusion of its product.