# Towards Business Partnership Recommendation Using User Opinion on Facebook

## TL;DR

This paper introduces a social media-based similarity model for businesses using Facebook user opinions, enabling the detection of business communities and potential partnerships through analysis of user reactions.

## Contribution

It presents a novel similarity model based on Facebook user opinions, along with algorithms for community detection and outlier identification among businesses.

## Key findings

- Analyzed approximately 280 million Facebook reactions.
- The model effectively identifies business communities.
- Potential to support strategic partnership recommendations.

## Abstract

The identification of strategic business partnerships can potentially provide competitive advantages for businesses; however, due to the dynamics and uncertainty present in business environments, this task could be challenging. To help businesses in this task, this study presents a similarity model between businesses that consider the opinions of users on content shared by businesses on social media. Thus, this model captures significant virtual relationships among businesses that are generated by users in the virtual world. Besides, we propose an algorithm for detecting business communities in the considered model. We also propose an algorithm to identify possible business outliers in the detected communities, which could represent an automatic way to identify non-obvious relations that might deserve particular attention of business owners. By exploring approximately 280 million user reactions on Facebook, we show that our results could favor the development of, for example, a new strategic business partnership recommendation service.