Abstract

The hashtag, a phrase that is highlighted by preceding it with a hash symbol (#), is already 6 years old. People use it on a massive scale in social media, with two objectives: to tag (or label) conversations and content, and to identify communities. It can be used also as a rhetorical element in activism, marketing, or just for amusement. Recent research highlights its value as a predictive system and for engaging the TV audience using Twitter. Some national and academic libraries are storing and preserving hashtags for future research.

Abstract

This research analyzes the use of Twitter by the four main Spanish political parties in the electoral campaign of December 2015. It delves into the tendencies of the tweets, published from the official accounts of the parties and the candidates, and those hashtags or tags that became national trending topics. It discovers that they emphasize the stylistic role of the candidate and use quinine humor, with the aim of humanizing the candidate and bringing him closer to the audience. According to the conclusions, getting the most virality does not ensure electoral victory, but the trends of the studied period yield interesting recommendations for political communication.

Abstract

Public television has a mission to promote debate around topics of public interest. Twitter is the social metamedia used by TV programs to fulfil this task online. This research analyzes the capability of public television to generate an effective debate through Twitter and also looks at the relationship between physical audience and social audience. We apply a quantitative methodology that employs our own capture and treatment technique to examine the activity generated by the hashtags proposed by six television programs on BBC One, TV3, and La 1. The main finding shows that these programs fail in their mission to generate a robust public debate in Twitter; instead the discussion is generated by a recurrent group of users that control the debate flow around their comments. Finally, the physical audience is not a predictive factor of the social audience.

Abstract

Twitter 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.