In era of global crises and data-based business competition, when users use social media, their personal data and network behaviors are collected. These data are valuable for making right decisions. Based on fair viewpoint, the profits of social platforms should be shared with the data providers. In order to discuss the applicability of profit sharing, 26 users were grouped and interviewed collaboratively. The customer profiles and value proposition maps were then used as a tool to summarize the respondents' preliminary suggestions to explore the users' motivation for using social network media and their opinions on the issues related to data collected, privacy, and profit sharing. This study has also explored the issues related to the fair and reasonable rewards of social platforms. Then, the profit-sharing models were designed according to the suggestions, which were obtained from 388 valid questionnaires. This study helps us to understand the common views of users of social media platforms on the collection and sharing of their data.
TopIntroduction
Due to the rise of web service models, user-oriented social media can support social activities, including communication, connection, interaction, and sharing. People’s lives have been closely related to social media. When using social media, users provide personal data and share all kinds of information, such as articles, pictures, videos and life details. Social media platforms can, therefore, easily collect all kinds of behavioral information about users, which can be used to analyze, understand and predict their preferences and browsing habits (as shown in Figure 1), as well as to establish the competitive intelligence of an enterprises (Nunes & Correia, 2013; Parker et al., 2016).
At present, personality trait analyses are carried out mainly by collecting the network behavior and using habits of users, in order to use accurate personalized advertisements to earn advertising fees. If they are properly analyzed, the big data hidden in social networks are potentially valuable for helping governments and enterprises to make the right decisions.
Many companies especially in the age of global competition are committed to big data analytics technology for exploring the consumption patterns and living habits and to provide fast and accurate smart marketing services. According to the results of big data analytics, some enterprises conduct business model innovations (Tykkyläinen & Ritala, 2020; Heider et al., 2020) and develop accurate network behavior-locking technologies.
In the current era of data economy, users ostensibly enjoy various online resources for free, but in fact, they are exchanging their private information for those free resources (Lee, 2017; Andrejevic, 2014). As users use social media every day to contribute to their personal behavioral data, at the same time, media platforms are collecting their data. Casilli (2017) noted that the use of the Internet has become digital work, and our posts, likes and shares on FB are of commercial value, with the users becoming free digital laborers. Hence, at present, there is no fair network profit sharing system, which is obviously unfair to the users.
Advanced countries have revised their personal data protection laws, in order to promote personal data availability and an open information business environment. The laws enable people to decide how, and to what extent, their personal data is to be used, and they even have the right to sell them.
Data have become an essential element in economic and commercial operations. Social platforms, just like a huge database, store the real condition of a user’s social activities on the Internet, which can then be accurately predicted (Pedersen & Ritter, 2020).
Because it was difficult to obtain data in the past, economists did not take it into account, when considering production factors. However, with the modern advanced technology, there are no limitations on data collection. Just like search engine Google, there seems to be a production line of raw data (raw material) input at one end and processed information and knowledge (product) output at the other end (Mayer-Schönberger & Cukier, 2013).
Therefore, the profits of social platforms should be shared with data providers, with the rewards being determined by their contribution. Fuchs (2010) proposed that the profits should be shared with the digital workers. It is, therefore, reasonable economic behavior to share the results of big data analytics with the data producers.
There are no studies on the profit sharing systems of social networks. Much of the literature only explores the behavior of social media users. Based on the above, this study explored the issue of fair and reasonable rewards for social network data providers, and designed two profit sharing models. Through this study can to balance the use and profits between users and data collectors, and for users to be willing to share their data, so that the big data industry can develop fast and their personal behavioral data can contribute to the economy or society in a safe environment.
Figure 1. Scenario of profit sharing models on social media