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Hilton Atlanta, 204
International Trade and Finance Association
Artificial Intelligence, Data Science and Economics at the Crossroads
Saturday, Jan. 5, 2019 8:00 AM - 10:00 AM
- Chair: Thierry Warin, SKEMA Business School
Data Science, Entrepreneurship, and Economic Inclusion
AbstractIn this day and age of technological acceleration, societies have to adapt. This presentation explores the impact of the so-called Industrial Revolution 4.0 on economic inclusion.
Shale Gaz Extraction in the United States: Perspectives from Geo-Located Twitter Conversations and Academic Publications
AbstractIn this article, we explore the contrast between the scientific publications about fracking and the potential questions about environmental and health impacts and the perception of the local population. The methodology used in this article is based on unstructured data from Twitter as well as scientific publications. NLP and sentiment analyses are used to extract polarity indices and sentiment categories. Mapping techniques are also extensively used to map all the shale gaz wells and the geo-located conversations on Twitter.
Computer Algorithms Prefer Headless Women
AbstractAdvertising algorithms power the online digital economy. However, it is unclear whether they may end up distorting the kind of information people are exposed to. To explore this we ran a randomized online ad campaign on Snapchat on behalf of a French computer science school that explored how the ad algorithm allocated pictorial content representing gender. Our results show that pictures depicting a complete male torso was shown more to teens, while the female picture that was displayed most by the algorithm depicted the woman as not having a head. We present suggestive evidence that these algorithms are driven by preferences in large population centers in Paris as it appears the algorithm determines which images are the most ``engaging'' on the first day for the places with the largest numbers of users and replicates this pattern going forward elsewhere.
Hukou System, Access to Health Services and Health Outcomes: A Machine Learning Approach Applied to Rural-Urban Migration in China
AbstractMachine learning is a new paradigm in Data Science. How can we use it to help us find new trends and explanations in migration datasets.
Nathalie de Marcellis,
City University of New York
University of Paris Sud
Institut Mines Telecom
Jonathan P. Allen,
University of San Francisco
- C8 - Data Collection and Data Estimation Methodology; Computer Programs
- A1 - General Economics