\u25c7<\/strong>BAIRAL<\/strong>\uff08<\/strong>B\u2019AI RA League<\/strong>\uff09 \u25c7Date & Venue Online: Zoom Meeting: Meeting ID: 849 7647 1596 \u25c7Guest Speaker \u25c7Abstract Can AI help social scientists overcome the challenges posed by the sheer volume of data?<\/span><\/p>\n The speaker explores this question by attempting to train AI models to accelerate the analysis of social media corpora. However, this raises a deeper issue: is AI truly a \u201ccollaborator\u201d in the research process, or merely a \u201cresearch assistant\u201d?<\/span><\/p>\n This talk will share a practical experience related to frame analysis.<\/span><\/p>\n \u25c7Organizer \u00a0\u25c7Inquiry \u25c7BAIRAL\uff08B\u2019AI RA League\uff09 BAIRAL is a study group by<\/p>\n
\n<\/strong>BAIRAL is a study group by young research assistants (RA) of the B\u2019AI Global Forum of the Institute for AI and Beyond at the University of Tokyo. Aiming to achieve gender equality and a guarantee of rights for minorities in the AI era, this study group examines relationships between digital information technology and society. BAIRAL organizes research meetings every other month with guest speakers in a variety of fields.<\/p>\n
\n<\/strong>\u30fbDate: Thursday, December 4, 2025, 3:00 \u2013 4:30 pm (JST)
\n\u30fbLanguage: English (No Translation)
\n<\/span>\u30fbVenue: In-person + Online hybrid\u00a0 (No registration required)
\n<\/span>In-person Venue: Room 327, Faculty of Science Bldg.3 (The University of Tokyo, Asano Campus)
\n<\/span>https:\/\/www.u-tokyo.ac.jp\/content\/400020145.pdf<\/span><\/a><\/p>\n
\n<\/span>https:\/\/u-tokyo-ac-jp.zoom.us\/j\/84976471596?pwd=Ajz19k7y3wZTgMyxVulRDYolVfoDTI.1<\/span><\/a><\/p>\n
\n<\/span>Passcode: 669682<\/span><\/p>\n
\n<\/strong>Dr. <\/span>Hui-Wen Liu<\/span>, Professor, Department of Communication<\/span>, <\/span>National Chengchi University (NCCU), Taiwan<\/span><\/p>\n
\n<\/strong>Since the rise of social media, social science researchers have faced an overwhelming amount of linguistic data. Traditional qualitative research methods then started struggling to keep up, particularly in terms of the speed for manual classification, annotation, and analysis.<\/span><\/p>\n
\n<\/b>B\u2019AI Global Forum, Institute for AI and Beyond at the University of Tokyo<\/span><\/p>\n
\n<\/b>Priya Mu (Research assistant of the B\u2019AI Global Forum)
\n<\/span>priya-mu[at]<\/span>g.ecc.u-tokyo.ac.jp<\/span><\/a> (Please change [at] to @)<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"