Towards Business Partnership Recommendation Using User Opinion on Facebook
This work addresses the challenge of recommending business partnerships for companies, but it appears incremental as it builds on existing social media analysis methods.
The study tackled the problem of identifying strategic business partnerships by developing a similarity model based on user opinions on Facebook content, and proposed algorithms for community detection and outlier identification, demonstrating potential with analysis of approximately 280 million user reactions.
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.