Grounding the Semantics of Part-of-Day Nouns Worldwide using Twitter
This work addresses the problem of understanding cross-cultural linguistic variability in temporal expressions for sociolinguists and computational linguists, but it is incremental as it applies existing methods to new Twitter data.
The researchers analyzed how part-of-day nouns like 'night' and their greetings vary across languages and cultures by mining multilingual tweets to study frequency patterns relative to local time, providing insights into semantic variations and cultural influences.
The usage of part-of-day nouns, such as 'night', and their time-specific greetings ('good night'), varies across languages and cultures. We show the possibilities that Twitter offers for studying the semantics of these terms and its variability between countries. We mine a worldwide sample of multilingual tweets with temporal greetings, and study how their frequencies vary in relation with local time. The results provide insights into the semantics of these temporal expressions and the cultural and sociological factors influencing their usage.