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Accepted Paper:

“Broken Whispers”: Isolating the Local in a Global Hashtag (#challengeaccepted) using ML classification  
Janani Ilamparithi (Anthropour)

Paper short abstract:

Hashtag brings with it a multiplicity of meanings with respect to socio-cultural and political factors of the 'local'. This enables anthropological research to develop a multi-sited research design that spans regions and time, aided by ML classification to study on a 'global' social media dataset.

Paper long abstract:

Unknown circumstances necessitate improvisation in the known framework. Conducting research on a digital network, this paper entails tracking the discourses and social transactions that take place within the network. Social media facilitates the transmission of individualistic experiences, and connects people from far and wide places through shared realities. Sharing experience includes passing on ‘broken’ meanings, and contextualising ‘whispers’ within our own time and space. This rate of flow of information is followed using multi-sited ethnographical framework, with an added skillset of ML analysis of the usage of hashtag #challengeaccepted.

What begins as a simple tagging or labelling of a post/message on the social media platform (using the hashtag), evolves into a larger collective discourse, with which others start engaging. Individuals who share their personal narratives become connected to the global context and become relatable to everyone else, in their own localised way. Hashtag activism gives a voice to the minority and the subordinated, where discourses are frequently polarised by the narratives of the majority, promoting plurality.

However, the larger question that the research paper addresses is how much social media is representative of the entire population. In the context of developing and under-developed nations, there are so many unheard and unregistered cases. The digital representation is farther away from the total. This bias is answered through lived experiences and anthropological perspective, knowing that data is triangulated by going a step further into qualitatively evidencing it.

Panel P34
Towards an algorithmic anthropology: What can AI add to the anthropologist's toolkit?
  Session 1 Friday 10 June, 2022, -