This repository contains data and information regarding the paper:
F. Bertone, L. Vassio, and M. Trevisan, “The Stock Exchange of Influencers: A Financial Approach for Studying Fanbase Variation Trends” Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2021, 0.1145/3487351.3488413
In many online social networks (OSNs), a limited portion of profiles emerges and reaches a large base of followers, i.e., the so-called social influencers. One of their main goals is to increase their fanbase to increase their visibility, engaging users through their content. In this work, we propose a novel parallel between the ecosystem of OSNs and the stock exchange market. Followers act as private investors, and they follow influencers, i.e., buy stocks, based on their individual preferences and on the information they gather through external sources. In this preliminary study, we show how the approaches proposed in the context of the stock exchange market can be successfully applied to social networks. Our case study focuses on 60 Italian Instagram influencers and shows how their followers short-term trends obtained through Bollinger bands become close to those found in external sources, Google Trends in our case, similarly to phenomena already observed in the financial market. Besides providing a strong correlation between these different trends, our results pose the basis for studying social networks with a new lens, linking them with a different domain.
In this work, we take as case study 60 Italian public figures popular in Instagram. For them, we collect historical data on their activity on Instagram as well as the search engine volume using Google Trends. The collected data on the two platforms span more than 3 years, from November 2017 to March 2021. We conduct our analysis on three categories of profiles: (i) Singers/Musicians, (ii) Athletes, and (iii) VIPs.
The list of used influencers can be downloaded at the following link: