Automated Author ProfileKyeong Jung, Jin
Department of Curriculum & Instruction
Kyeong Jung, Jin
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.9 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
We examined how African and Asian immigrants (re)present the interplay of identities and experiences across digital narratives composed and shared on TikTok. We found content creator’s digital narratives to be illustrative of their transbordered algorithmic identities. We draw on and extend BlackCrit and AsianCrit, and African and Asian onto-axio epistemologies Ubuntu and 정(Jeong) to contextualize and define transbordered algorithmic identities as leveraging social media to build community with those who share experiences across identities and geographies; complicating static notions of home, place, rootedness, and memories of being, with, and among; and navigating discursive and geographic borders while negotiating presentations of individuals shaped by online interactions and encounters with digital algorithms that curate content, suggest connections, and analyze online practices. We conclude with implications for research and teaching.
Data can be found in the “Algorithmic Identities data and analysis” file.
Authors
- Watson, Vaughn W. M. ;
- Michigan State University ;
- Kyeong Jung, Jin ;
- Berends, Joel E. ;
- Michigan State University ;
- Boateng, Sandra ;
- Michigan State University ;
- Allene Hall, Lindsey ;
- Grand Valley State University
We examined how African and Asian immigrants (re)present the interplay of identities and experiences across digital narratives composed and shared on TikTok. We found content creator’s digital narratives to be illustrative of their transbordered algorithmic identities. We draw on and extend BlackCrit and AsianCrit, and African and Asian onto-axio epistemologies Ubuntu and 정(Jeong) to contextualize and define transbordered algorithmic identities as leveraging social media to build community with those who share experiences across identities and geographies; complicating static notions of home, place, rootedness, and memories of being, with, and among; and navigating discursive and geographic borders while negotiating presentations of individuals shaped by online interactions and encounters with digital algorithms that curate content, suggest connections, and analyze online practices. We conclude with implications for research and teaching.
Data can be found in the “Algorithmic Identities data and analysis” file.
Authors
- Watson, Vaughn W. M. ;
- Michigan State University ;
- Kyeong Jung, Jin ;
- Berends, Joel E. ;
- Michigan State University ;
- Boateng, Sandra ;
- Michigan State University ;
- Allene Hall, Lindsey ;
- Grand Valley State University
We examined how African and Asian immigrants (re)present the interplay of identities and experiences across digital narratives composed and shared on TikTok. We found content creator’s digital narratives to be illustrative of their transbordered algorithmic identities. We draw on and extend BlackCrit and AsianCrit, and African and Asian onto-axio epistemologies Ubuntu and 정(Jeong) to contextualize and define transbordered algorithmic identities as leveraging social media to build community with those who share experiences across identities and geographies; complicating static notions of home, place, rootedness, and memories of being, with, and among; and navigating discursive and geographic borders while negotiating presentations of individuals shaped by online interactions and encounters with digital algorithms that curate content, suggest connections, and analyze online practices. We conclude with implications for research and teaching.
Data can be found in the “Algorithmic Identities data and analysis” file.
Authors
- Watson, Vaughn W. M. ;
- Michigan State University ;
- Kyeong Jung, Jin ;
- Berends, Joel E. ;
- Michigan State University ;
- Boateng, Sandra ;
- Michigan State University ;
- Allene Hall, Lindsey ;
- Grand Valley State University