Transitude: Machine Translation on Social Media: MT as a potential tool for opinion (mis)formation (2024)

Abstract: Misinformation on social media is a concern for content creators, consumers and regulators alike. Transitude looks at misinformation generated by machine translation (MT) through distortion of the intention and sentiment of text. It is the first study of MT’s impact on the formation of users’ views of society through refugees in Ireland. It extends current MT evaluation methods with a new quality evaluation framework, producing the first dataset annotated for information distortion. It provides insights into the risks of relying on MT, with recommendations for users, developers, and policymakers.

## previous research the spread of misinformation on social media has attracted collective efforts nationally and internationally. for example, the irish government proposed the 2020 online safety and media regulation bill to regulate online activities and tackle harmful content. however, such initiatives focus on source texts, overlooking machine translation (mt) use, which is embedded into social media platforms. mt as a translation tool carries risks in terms of misinformation as it can sometimes deliver misleading translation where the meaning becomes different from what was intended, leading to major consequences. for example, facebook's mt once provided 'attack them' as a translation for 'good morning', prompting the israeli police to arrest the palestinian author of the message. 1 highlighting the need to consider mt and its implications is vital for any multilingual/multicultural society. recent humanitarian crises such as the syrian refugee crisis emphasised the importance of communication and the consequences of misinformation. these populations rely on mt to stay informed @xcite . commercial mt systems are not trained on conversational user-generated content (ugc), which is mostly written in colloquial, abbreviated language, using symbols and hashtags @xcite . previous research revealed that mt tends to generate critical errors when translating ugc (al @xcite . social media posts often contain political or social opinions, expressed with a specific purpose @xcite . such content depends heavily on persuasive language to influence opinions, and employs irony, sarcasm and/or metaphor. however, there is no guarantee that mt preserves the intention and sentiment of the original. as a result, readers of the translation may form a different opinion to the one intended. transitude's research objectives (ro) are: 1. provide an account of mt's role in information sharing on social media. 2. estimate mt's role in forming asylum seekers and refugees' views of, and attitudes towards, a new society. 3. propose recommendations on how the risks of using mt can be mitigated. ## research design and methodology transitude employs analytical frameworks, drawing on translation studies models (text in context, focusing on intentionality and sentiment) @xcite ) that are typically used to judge human translation, and natural language processing techniques (keyword extraction and automatic sentiment analysis). target participants are arabic-speaking syrian and iraqi asylum seekers and refugees (as&rs) living in ireland.