Financial Data Science

A new discipline emerges - “Financial Data Science” - which combines approaches from data mining and financial statistics leveraging large-scale data processing, machine learning, statistics, and financial modeling.

Nowadays the Internet, as a major platform for communication and information exchange, provides a rich repository of people’s opinion and sentiment about a vast spectrum of topics. Such knowledge is embedded in multiple facets, such as comments, tags, browsing actions, as well as shared media objects. The analysis of such information either in the area of opinion mining, affective computing or sentiment analysis plays an important role in behavior sciences, which aims to understand and predict human decision making and enables applications such as brand monitoring, stock market prediction, or political voting forecasts.

This ubiquity of online content conveys much about our thinking and feeling, in that it reflects our personal values and ourselves as a society. Inspired by the ACM SIGKDD 2014 conference titled: Data Mining for Social Good and Bloomberg’s CTO Shawn Edwards statement: ”Data scientists have a tremendous opportunity to contribute to the most pressing problems faced by policy makers today.”, we see the advent of a new discipline: Financial Data Science.

In this particular context, we would like to address the challenging task to mine social multimedia for environmental and social impact assessments. First and foremost, the understanding of a society’s views and concerns towards themes such as environmental issues (pollution, climate change) or societal issues (gender equality, human rights, child labor) is a crucial prerequisite in forming a democratic government. Nevertheless, of equal importance is the fact that philanthropists and impact investors fund hundreds of initiatives supporting the PRI’s and UNGC’s principles around the world without having instant evidence about the actual social and environmental impact. With the recent ubiquity of content on social media platforms such as e.g. Twitter, Flickr, and YouTube, Multimedia Opinion Mining for Social Good should be in a position to address this challenge.