Catalina-García, BeatrizSuárez-Álvarez, Rebeca2023-12-272023-12-272022-10-10Catalina-García, Beatriz; Suárez-Álvarez, Rebeca (2022). “Twitter interaction between audiences and influencers. Sentiment, polarity, and communicative behaviour analysis methodology”. Profesional de la información, v. 31, n. 6, e310618.1699-2407https://hdl.handle.net/10115/28015Twitter is one of several social networks with the highest numbers of users in Spain. In spite of this, how are communicative relationships developed in the digital environment among influencers who have emerged on the Internet? These personalities have a stronger influence on children and young people than traditional celebrities. The aim of this work is to study the communicative interaction generated on the profiles of Spanish influencers with the most followers on Twitter, based on the number of content items generated and the responses they receive from users. The polarity and sentiment conveyed by these communications have also been analysed. By processing publications in real time using machine learning based on sentiment analysis, 48,878 tweets and retweets from five influencers were studied over a period of 40 days. The results show that the publications reached nearly 200 million followers, and despite being fourth in terms of the number of followers, @IbaiLlanos is the influencer who leads the conversations on Twitter with the highest number of tweets, retweets, and audience share. Among the most popular topics, sporting events stand out. This study has also confirmed that the most frequently stated emotion is surprise, and that positive messages prevail over those that are negative and neutral with regard to polarity. Nevertheless, the linear regression data has verified that the main trend is toward publishing negative messages, with a lower statistical correlation, which is a behaviour that might possibly be duplicated on other social networks.engAttribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/TwitterAudiencesInfluencersSentiment analysisParasocial interactionPolarityEmotionsCommunicationSocial networksSocial mediaHashtagsTheoretical advanceMethodologyinfo:eu-repo/semantics/article10.3145/epi.2022.nov.18info:eu-repo/semantics/openAccess