Automated Author ProfileReynoso, Diego
Reynoso, Diego
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: 2.8 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Selective avoidance, defined as the tendency to evade information that challenges political beliefs, weakens deliberative norms in polarized societies. Most studies have focused on the United States and Europe, often attributing avoidance to algorithmic curation. This article examines Argentina, one of the most polarized countries in Latin America, to assess the broader validity of these explanations. Using survey data from ESPOP 2024, we analyze how ideological extremism, partisan identification, political sophistication, and voting intention shape avoidance online and offline. Logistic regression models show that strong partisan ties, extreme ideological views, and greater sophistication significantly increase the likelihood of avoidance. Cognitive Partisans, who combine high sophistication with strong partisan identity, are the most prone to filtering, suggesting that political knowledge enables strategic selectivity rather than openness. Comparative evidence from Argentina demonstrates that selective avoidance reflects identity-protective processes not limited to advanced democracies or digital environments.
Authors
- Reynoso, Diego
Selective avoidance, defined as the tendency to evade information that challenges political beliefs, weakens deliberative norms in polarized societies. Most studies have focused on the United States and Europe, often attributing avoidance to algorithmic curation. This article examines Argentina, one of the most polarized countries in Latin America, to assess the broader validity of these explanations. Using survey data from ESPOP 2024, we analyze how ideological extremism, partisan identification, political sophistication, and voting intention shape avoidance online and offline. Logistic regression models show that strong partisan ties, extreme ideological views, and greater sophistication significantly increase the likelihood of avoidance. Cognitive Partisans, who combine high sophistication with strong partisan identity, are the most prone to filtering, suggesting that political knowledge enables strategic selectivity rather than openness. Comparative evidence from Argentina demonstrates that selective avoidance reflects identity-protective processes not limited to advanced democracies or digital environments.
Authors
- Reynoso, Diego