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This paper presents a multilingual study on, per single post of microblog text, (a) how much can be said, (b) how much is written in terms of characters and bytes, and (c) how much is said in terms of information content in posts by different organizations in different languages. Focusing on three different languages (English, Chinese, and Japanese), this research analyses Weibo and Twitter accounts of major embassies and news agencies. We first establish our criterion for quantifying how much can be said in a digital text based on the openly available Universal Declaration of Human Rights and the translated subtitles from TED talks. These parallel corpora allow us to determine the number of characters and bits needed to represent the same content in different languages and character encodings. We then derive the amount of information that is actually contained in microblog posts authored by selected accounts on Weibo and Twitter. Our results confirm that languages with larger character sets such as Chinese and Japanese contain more information per character than English, but the actual information content contained within a microblog text varies depending on both the type of organization and the language of the post. We conclude with a discussion on the design implications of microblog text limits for different languages.
The objective of the study is to examine coronavirus disease (COVID-19) related discussions, concerns, and sentiments that emerged from tweets posted by Twitter users. We analyze 4 million Twitter messages related to the COVID-19 pandemic using a lis
Past research has studied social determinants of attitudes toward foreign countries. Confounded by potential endogeneity biases due to unobserved factors or reverse causality, the causal impact of these factors on public opinion is usually difficult
The past several years have witnessed a huge surge in the use of social media platforms during mass convergence events such as health emergencies, natural or human-induced disasters. These non-traditional data sources are becoming vital for disease f
The spread of COVID-19 has sparked racism, hate, and xenophobia in social media targeted at Chinese and broader Asian communities. However, little is known about how racial hate spreads during a pandemic and the role of counterhate speech in mitigati
In addition to posting news and status updates, many Twitter users post questions that seek various types of subjective and objective information. These questions are often labeled with Q&A hashtags, such as #lazyweb or #twoogle. We surveyed Twitter