Multi-modal analysis of 994 Weibo posts and 18,966 images finds sentiment as the sole consistent predictor of censorship, with anti-government topics deleted more often and average deletion time of three hours.
Linguistic Characteristics of Censorable Language on SinaWeibo
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abstract
This paper investigates censorship from a linguistic perspective. We collect a corpus of censored and uncensored posts on a number of topics, build a classifier that predicts censorship decisions independent of discussion topics. Our investigation reveals that the strongest linguistic indicator of censored content of our corpus is its readability.
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cs.SI 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
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Assessing Post Deletion in Sina Weibo: Multi-modal Classification of Hot Topics
Multi-modal analysis of 994 Weibo posts and 18,966 images finds sentiment as the sole consistent predictor of censorship, with anti-government topics deleted more often and average deletion time of three hours.