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Tribune News Network
Doha
A student from Hamad Bin Khalifa University’s (HBKU) College of Science and Engineering (CSE) was among the winners at the 2019 workshop on NLP4IF co-located with Empirical Methods in Natural Language Processing (EMNLP) held in Hong Kong recently.
Shehel Yoosuf, a Masters in Data Science and engineering student working under the guidance of Dr David Yang, leading a QNRF-funded project on Fraudulent Message Detection Under Differential Privacy, developed the best performing system in the AI-driven fine grained propaganda detection task.
More than 15 international teams over a period of 2 months worked on developing Machine Learning models capable of finding every instance of propaganda from a set of news articles.
The participant’s system was required to specify the phrase where propaganda occurs and also determine the type of propaganda utilised from a list of 18 techniques.
Categories for the latter task included ‘appeal to authority’, ‘bandwagons’ and ‘black and white fallacy.’
Speaking after receiving the award, Shehel said, “It was an honour to represent HBKU in the competition and present the solution in the workshop. I enjoyed the challenge of working on such a relevant problem as propaganda which is becoming widespread with the prevalence of web media. I’m grateful to CSE for providing me with this opportunity and resources to make it happen.”
Dr Mounir Hamdi, dean of CSE, said: “We’re delighted that one of our students excelled in the conference’s propaganda detection competition. The standard of contestants was high, as were their abilities to cope with the demands of this task. Shehel’s success underscores CSE’s growing reputation as a world-class place to study science, engineering and technology.”
Doha
A student from Hamad Bin Khalifa University’s (HBKU) College of Science and Engineering (CSE) was among the winners at the 2019 workshop on NLP4IF co-located with Empirical Methods in Natural Language Processing (EMNLP) held in Hong Kong recently.
Shehel Yoosuf, a Masters in Data Science and engineering student working under the guidance of Dr David Yang, leading a QNRF-funded project on Fraudulent Message Detection Under Differential Privacy, developed the best performing system in the AI-driven fine grained propaganda detection task.
More than 15 international teams over a period of 2 months worked on developing Machine Learning models capable of finding every instance of propaganda from a set of news articles.
The participant’s system was required to specify the phrase where propaganda occurs and also determine the type of propaganda utilised from a list of 18 techniques.
Categories for the latter task included ‘appeal to authority’, ‘bandwagons’ and ‘black and white fallacy.’
Speaking after receiving the award, Shehel said, “It was an honour to represent HBKU in the competition and present the solution in the workshop. I enjoyed the challenge of working on such a relevant problem as propaganda which is becoming widespread with the prevalence of web media. I’m grateful to CSE for providing me with this opportunity and resources to make it happen.”
Dr Mounir Hamdi, dean of CSE, said: “We’re delighted that one of our students excelled in the conference’s propaganda detection competition. The standard of contestants was high, as were their abilities to cope with the demands of this task. Shehel’s success underscores CSE’s growing reputation as a world-class place to study science, engineering and technology.”
