Name
Abstract | ||
|---|---|---|
Political polarization can emerge on electoral campaigns where the population faces a dichotomous decision, with only two voting alternatives. In this paper, we analyze the Twitter conversation around the second round of the 2017 Chilean elections, where voters had to choose between the final two candidates. First, we have estimated the opinions of Twitter users obtaining a distribution of opinions for each day. Next, we have measured the resulting political polarization from the cited opinion distributions and track its evolution during a full week that includes the voting day. We found the conversation to be highly polarized, reaching its maximum during the previous day to the election and significantly decreasing the day after due to the presence of new users who only participated during that day. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1155/2019/5854037 | COMPLEXITY |
Field | DocType | Volume |
Social psychology,Population,Conversation,Voting,Artificial intelligence,Polarization (politics),Mathematics,Machine learning | Journal | 2019 |
ISSN | Citations | PageRank |
1076-2787 | 1 | 0.36 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gastón Olivares | 1 | 3 | 1.54 |
| Juan Pablo Cárdenas | 2 | 3 | 1.54 |
| Juan Carlos Losada | 3 | 56 | 7.08 |
| J Borondo | 4 | 73 | 4.78 |