Montgomery & Company (MoCo) is a weekly podcast and radio show hosted by two-time WNBA Champion and Co-Owner/Vice President of the Atlanta Dream, Renee Montgomery, in partnership with WABE Atlanta. Both insightful and compelling, MoCo features interviews with some of the world’s top athletes, entertainers, and innovators as well as roundtable discussions with Renee’s colleagues, friends, and family, about sports, culture and building generational wealth. Montgomery & Company: Sports, Cultu ...
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Sisällön tarjoaa MIT Comparative Media Studies/Writing and Massachusetts Institute of Technology. MIT Comparative Media Studies/Writing and Massachusetts Institute of Technology tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.
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Desmond Upton Patton: “Contextual Analysis of Social Media”
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Manage episode 254165380 series 1053864
Sisällön tarjoaa MIT Comparative Media Studies/Writing and Massachusetts Institute of Technology. MIT Comparative Media Studies/Writing and Massachusetts Institute of Technology tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.
While natural language processing affords researchers an opportunity to automatically scan millions of social media posts, there is growing concern that automated computational tools lack the ability to understand context and nuance in human communication and language. Columbia University’s Desmond Upton Patton introduces a critical systematic approach for extracting culture, context and nuance in social media data. The Contextual Analysis of Social Media (CASM) approach considers and critiques the gap between inadequacies in natural language processing tools and differences in geographic, cultural, and age-related variance of social media use and communication. CASM utilizes a team-based approach to analysis of social media data, explicitly informed by community expertise. The team uses CASM to analyze Twitter posts from gang-involved youth in Chicago. They designed a set of experiments to evaluate the performance of a support vector machine using CASM hand-labeled posts against a distant model. They found that the CASM-informed hand-labeled data outperforms the baseline distant labels, indicating that the CASM labels capture additional dimensions of information that content-only methods lack. They then question whether this is helpful or harmful for gun violence prevention.
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407 jaksoa
MP3•Jakson koti
Manage episode 254165380 series 1053864
Sisällön tarjoaa MIT Comparative Media Studies/Writing and Massachusetts Institute of Technology. MIT Comparative Media Studies/Writing and Massachusetts Institute of Technology tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.
While natural language processing affords researchers an opportunity to automatically scan millions of social media posts, there is growing concern that automated computational tools lack the ability to understand context and nuance in human communication and language. Columbia University’s Desmond Upton Patton introduces a critical systematic approach for extracting culture, context and nuance in social media data. The Contextual Analysis of Social Media (CASM) approach considers and critiques the gap between inadequacies in natural language processing tools and differences in geographic, cultural, and age-related variance of social media use and communication. CASM utilizes a team-based approach to analysis of social media data, explicitly informed by community expertise. The team uses CASM to analyze Twitter posts from gang-involved youth in Chicago. They designed a set of experiments to evaluate the performance of a support vector machine using CASM hand-labeled posts against a distant model. They found that the CASM-informed hand-labeled data outperforms the baseline distant labels, indicating that the CASM labels capture additional dimensions of information that content-only methods lack. They then question whether this is helpful or harmful for gun violence prevention.
…
continue reading
407 jaksoa
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