This Small Business Innovation Research Phase I project will build a novel software system to provide real-time social data analytics that will help people assess trust levels in the on-line sharing economy. In the sharing economy, two people who don't necessarily know each other trade goods or services on-line. Lack of trust among participants is one of the challenges that the sharing economy needs to resolve. Existing methods are too expensive (e.g. FICO score) or too inflexible (e.g. Facebook APIs) to serve the various types of on-line sharing markets. This project will provide a software system to process/display real time social analytics for each target market so that it can show the common background between two participants (e.g. a friend's friend, or from the same school, or from the same workplace, etc.) The more common background two people have, the more comfortable they are likely to feel in completing a transaction. The main technical challenge is to provide real time results while guaranteeing flexibility in adding social datasets to previously-collected datasets. This project will solve these challenges by using Graph Database and associated matching algorithms. Compared to SQL (Structured Query Language), Graph Database is faster (no JOINs) and allows easier addition of new datasets (no SCHEMAs).
The broader impact/commercial potential of this project is to grow the sharing economy by providing a mechanism to resolve the lack of trust. The sharing economy is currently a $3.5 billion market, growing at 25% annually, with the potential to grow to $26 billion. This developing marketplace will create new jobs, as evidenced by companies such as AirBnB (sharing rooms) and RelayRides (sharing cars). The sharing economy is beneficial for society since it encourages the re-use of assets that would otherwise be underutilized, allowing asset owners to recover some value and minimizing environmental waste. As noted in many articles, lack of trust among participants is one of the biggest challenges to growing the sharing economy. This project will help build trust among participants by revealing their existing personal connections in real time. Furthermore, data accumulated over time can potentially be used to reduce the high insurance premiums that currently apply to commerce in the sharing economy. If the probability of a negative outcome (i.e. the insurance risk) can be tied to the common background between two participants in an on-line transaction, then the trust measure that is proposed here can be used as a novel metric to underwrite an insurance product.
