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PyData Bratislava #16 [FIIT STU Edition]
22. mája 2019 @ 18:00 - 20:00
Talk Title: “Data-driven Approaches for Detection of Antisocial Behavior”
Description: Fake news, fake reviews, hating or trolling are the most prominent examples of online antisocial behavior which is currently present across the whole web. Growing negative consequences of such negative behavior have recently elicited many efforts, which are aimed at its characterization, detection and mitigation.
At first in our talk, we will shortly describe how the state-of-the-art data-driven techniques (especially AI, ML, data mining, NLP) can be applied in fighting antisocial behavior. We will highlight the most challenging open problems, such as a lack of suitable rich datasets or useful end-user services as well as bad interoperability of detection methods.
Secondly, we will introduce our solution how to overcome the stated open problems. We are working on a novel, universal and easily extensible platform named Monant. Our platform provides features for web monitoring, interfaces for AI classification and detection methods as well as for end-ser services (e.g. how to train users to detect fake news).
In more details, we will discuss its architecture and current state of implementations using many Python libraries for web crawling/parsing, scheduling extractions, API communication between main platform modules, etc.
Speaker/Bio: Ivan Srba, Róbert Móro, Veronika Žatková
Ivan and Róbert are researchers from FIIT STU in Bratislava leading two research projects aimed at online antisocial behavior detection. Veronika is a member of student team which worked on development of platform Monant.
LinkedIn: https://sk.linkedin.com/in/ivansrba, https://sk.linkedin.com/in/robom, https://sk.linkedin.com/in/veronika-%C5%BEatkov%C3%A1
@Meetup.com group’s event here (https://www.meetup.com/PyData-Bratislava/events/261382886) & @Eventbrite registration here (https://www.eventbrite.com/e/pydata-bratislava-meetup-16-fiit-stu-edition-tickets-61738006038) (if you use both your seat is guarateed). +our event you can find also @Facebook here (https://www.facebook.com/events/436165403628145/).
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Language of the event: Python, English
PyData Bratislava [Python Data Enthusiasts and Users, Data Scientists & Statisticians of all levels from Slovakia]
This meetup group is for Data Scientists, Statisticians, Economists and Data Enthusiasts using Python for data analysis and data visualization. The goals are to provide Python enthusiasts a place to share ideas and learn from each other about how best to apply the language and tools to ever-evolving challenges in the vast realm of data management, processing, analytics, and visualization.
PyData is a group for users and developers of data analysis tools to share ideas and learn from each other. We gather to discuss how best to apply Python tools, as well as those using R and Julia, to meet the evolving challenges in data management, processing, analytics, and visualization. PyData groups, events, and conferences aim to provide a venue for users acrossall the various domains of data analysis to share their experiences and their techniques. PyData is organized by NumFOCUS.org, a 501(c)3 non-profit in the United States.
The PyData Code of Conduct governs this meetup. To discuss any issues or concerns relating to the code of conduct or the behavior of anyone at a PyData meetup, please contact the organizer or NumFOCUS Executive Director Leah Silen (+1512-222-5449; email@example.com).
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GapData Institute (https://www.gapdata.org/) (GDI) is a nonprofit nonpartisan research institution harnessing power of data & wisdom of economics for public good.
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NumFOCUS (http://www.numfocus.org/) is a 501(c)(3) nonprofit that supports and promotes world-class, innovative, open source scientific computing. The mission of NumFOCUS is to promote sustainable high-level programming languages, open code development, and reproducible scientific research. We accomplish this mission through our educational programs and events as well as through fiscal sponsorship of open source data science projects. We aim to increase collaboration and communication within the scientific computing community.
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