On the one hand, AI-powered technologies have the potential to enhance online engagement and cultural exchange, providing new and innovative ways for Desi individuals to connect with others who share similar cultural interests.
However, there is a dearth of research on the intersection of Desi culture and AI on Twitter. This paper seeks to address this gap, examining the ways in which AI-powered technologies are being used to create, disseminate, and engage with Desi content on the platform.
Thirdly, the study identified several challenges related to the use of AI on Twitter, including issues related to bias, misinformation, and cultural sensitivity. For example, it was found that some AI-powered accounts on Twitter were spreading misinformation and stereotypes about Desi culture. desi ai twitter
This study used a mixed-methods approach, combining both qualitative and quantitative data collection and analysis methods. Twitter data was collected using the Twitter API, with a focus on hashtags related to Desi culture (e.g. #Desi, #Bollywood, #Cricket). A total of 10,000 tweets were collected over a period of two months.
On the other hand, the study highlights several challenges related to the use of AI on Twitter, including issues related to bias, misinformation, and cultural sensitivity. These challenges must be addressed in order to ensure that AI-powered technologies are used in a responsible and culturally sensitive manner. On the one hand, AI-powered technologies have the
The findings of this study have significant implications for our understanding of the intersection of Desi culture and AI on Twitter. The use of AI-powered technologies to create and disseminate Desi content on Twitter presents both opportunities and challenges.
Kim, J. (2018). AI-powered chatbots on social media: A study of user engagement. Journal of Interactive Marketing, 42, 1-15. Thirdly, the study identified several challenges related to
The collected data was then analyzed using a combination of natural language processing (NLP) techniques and content analysis. NLP techniques were used to identify patterns and trends in the data, while content analysis was used to examine the themes and topics present in the tweets.