Twitter @Jennifer Pan: 2022-01-10~2022-01-16

2022-01-14 作者: jenjpan 原文 #Twitter 的其它文章

Stanford Prof. China, authoritarian politics, political communication, computational social science, book at: https://t.co/xwSmruE99r

1: 2022-01-12 02:06:35+08:00 推文

“The Pervasive Presence of Chinese Government Content on Douyin Trending Videos” w/ @YingdanL_kk shows >40% of trending videos on Douyin (Chinese version of TikTok) come from Chinese gov’t, CCP, & official media accounts (what we call regime-affiliated accounts). 🧵


Yingdan_Lu: Excited to publish my first image-as-data paper with @jenjpan! We combine analysis of video, text and metadata to examine 50K Douyin Trending videos, and find the pervasive presence of the Chinese regime to compete for attention. Also enjoyed all amazing works in this SI, yay!
https://twitter.com/CCR_OpenJournal/status/1472944894645874692

2: 2022-01-12 02:06:36+08:00 推文

Re Trending videos from regime-affiliated accounts look and feel more like videos from celebrities & influencers (e.g., contain attention-maximizing feature like super short duration, high entropy) than videos from non-official media.

3: 2022-01-12 02:06:37+08:00 推文

Re Instead, videos contain human interest stories, stories about positive energy (ordinary people doing good/moral stuff), entertainment, & breaking news completely unrelated to any aspect of the Chinese gov’t or CCP.

4: 2022-01-12 02:06:38+08:00 推文

Re Do we see so much non-propaganda content because this is a proactive strategy (i.e., such videos are boosted to Trending) or because users like this content more (i.e., videos trend organically)? Early evidence suggests the former.

5: 2022-01-12 23:09:13+08:00 推文

Re @Miranda625 @YingdanL_kk We’ve thought about it but nothing concrete. Good to know there’s interest.

6: 2022-01-14 05:50:47+08:00 推文

Re @BruleRachel @fr_jensenius @BrownPhDGirl @prof_mirya @dawn_teele @tiffanydbarnes @jennpiscopo @dianazobrien @jenniferbussell @Pavithra_Suri @tara_slough @bhumipurohit For undergrad methods classes, I do data partnerships w/ local nonprofits: they share their data; students work with this data to learn concepts and R; students present findings back to nonprofit at end of quarter (e.g., poster session)


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