Exploring Echo Chambers in Twitter during Two Spanish Regional Elections: An Analysis of Community Interactions

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Number of interactions between community blocks.

Twenty most common words on user bios and in tweets on the total dataset (Madrid).

Twenty most common words on user bios and in tweets on the total dataset (Andalusia).

Number of interactions with certain active/passive user.

Coefficients between votes, and community users and interactions (Andalusia).

Number of interactions between community blocks by reply-type tweet.

Separation of tweets by Keyword/Hashtag type (Madrid).

Number of interactions grouping by political blocks.

Separation of tweets by keyword/hashtag type (Andalusia).

Most relevant users in each community (higher in-degree) (Andalusia).

Sentiment analysis by active users’ community (Andalusia).

RT Coverage table.

Number of interactions between community blocks by general-type tweet.

Tweet distribution over datasets.

Number of interactions between community blocks by RT-type tweet.

Most common words in users’ tweets by community (highlighted words with associated insights) (Madrid).

Number of users in each political community (Madrid).

Most common words in users’ bio by community (highlighted words with associated insights) (Madrid).

Sentiment analysis by active users’ community (Madrid).

#19J 2022 Andalusia election results.

Tweet distribution by type (and percentage) over datasets.

Number of users in each political community (Andalusia).

Number interactions (active and passive) for each community (Andalusia).

#4M 2021 Madrid election results.

Network-directed graph metrics.

Hashtags and keywords captured during the Madrid #4M 2021 electoral campaign period.

Most common words in users’ bio by community (highlighted words with associated insights) (Andalusia).

Most relevant users in each community (higher in-degree) (Madrid).

Number interactions (active and passive) for each community (Madrid).

Hashtags and keywords captured during the Andalusia #19J 2022 electoral campaign period

Most common words in users’ tweets by community (highlighted words with associated insights) (Andalusia).

Coefficients between votes, and community users and interactions (Madrid).

Number of interactions between community blocks by quote-type tweet.

Number of tweets separating by type of keyword/hashtag.