Abstract

 En este trabajo se presenta una propuesta basada en el “sentiment analysis” en medios sociales y orientada a la gobernanza digital en el marco de las ciudades inteligentes. Este sistema, después de seleccionar un grupo de temas relacionados con las preocupaciones de las personas acerca de la vida diaria en las ciudades, hace uso del léxico Afinn dado que el diccionario aplica una puntuación a cada palabra individual con el fin de reconocer y medir la fuerza de cada una. El experimento recupera tuits, clasificados por hashtags en una base de datos y, para cada uno de ellos, calcula el “sentimiento”. Esto implica el uso de procesos estadísticos para el reconocimiento del “sentimiento” como: el cálculo de la media ponderada, la desviación estándar y la distribución entre -5 a +5, el rango de puntuación usado por el léxico. Finalmente, se realiza una evaluación humana con el objetivo de comparar los resultados derivados del sistema automático. AbstractThis paper presents a method for analyzing social media and digital governance in smart cities. This research, after selecting a group of issues related to people’s concerns about daily life in cities, makes use of Afinn lexicon as dictionary with sentiment score in order to recognize and measure the strength of individual words. The experiment retrieves different tweets classified by hashtags in a database and calculates an average sentiment. It involves some statistical processes for the recognition of the topics’ sentiment: the calculation of the weighted average, the standard deviation, and the distribution among -5 to +5, based on the score range used by the lexicon. Finally, human evaluation is used to compare results from the automatic system.   

Abstract

The rapid adoption of social media by public administrations deserves attention from the side of institutional information and communication. One of the points recently identified is the tone used by public sector organizations to deliver their messages, as it may encourage citizen collaboration and participation. This paper explores the tone that Spanish city councils with more than 50,000 inhabitants are using in their social media profiles. This paper is based in two research questions: (a) What is the general tone used by the city councils in their use of social media?; (b) What explanatory factors are behind the adoption of one tone or another? Studying Twitter through big data techniques and statistical analysis, this study finds a positive general communicative tone. Traditional organizational, institutional and environmental factors do not seem to have a statistical significant influence over the tone. This article concludes with proposals for improvement on future research derived from the research results.

Abstract

This study proposes alternative measures of infotainment’s effects on audience perception and reception of news on social media, focusing on infotainment coverage of North Korea. We determine the elements of framing strategies and narrative styles in facilitating public attention, positive and negative responses, and engagement in news content. We used the YouTube application programming interface to collect data from VideoMug, Korea’s most popular YouTube channel, run by the Seoul Broadcasting System. We examined 23,774 replies commenting on North Korea-related video clips from July 1, 2018, to May 17, 2019. The findings show that entertainment and human interest frames were effective in drawing public attention to news coverage about North Korea. Using humor and colloquial language facilitated public attention (both positive and negative) and public engagement. Over half (59.55%) of the comments generated positive emotions; less than one-third generated negative emotions (31.41%); and a few generated neutral ones (9.03%). The infotainment approach helped make South Koreans’ attitudes toward North Korea and inter-Korean relations more positive. A small number of users who served as top authorities were extremely partisan and conducted intense debates about infotainment practices. This study’s hybrid analytical framework using computerized text mining techniques offers both theoretical and methodological insights into the function of infotainment in the context of social media.

Abstract

Social networks have become a major communication channel for organizations, including those focused on security and defense. This article specifically examines how the Spanish Armed Forces and State Security Forces communicate on Twitter, with the aim of analyzing the factors that influence engagement with their tweets. A model validated with a sample of 14,540 tweets shows the role that a series of variables related to rational and emotional communication attributes has. These variables are estimated utilizing techniques such as Python and VBA. Subsequently, a logistic model using IBM SSPS estimates the effect of each variable on the probability that a tweet will lead to more or less engagement. The results show that followers of military accounts, such as the Army, tend to have higher rates of interaction than followers of other accounts, even though military accounts have fewer total followers than police accounts. Furthermore, the results confirm the importance of using both rational and emotional stimuli for a message to be effective. To increase engagement, information provided by organizations should use elements such as hyperlinks, emojis, and photographs, and refer to topics that appeal to individuals’ emotions, such as patriotism.

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.

Abstract

Public bike share (PBS) systems are meant to be a sustainable urban mobility solution in areas where different travel options and the practice of active transport modes can diminish the need on the vehicle and decrease greenhouse gas emission. Although PBS systems have been included in transportation plans in the last decades experiencing an important development and growth, it is crucial to know the main enablers and barriers that PBS systems are facing to reach their goals. In this paper, first, sentiment analysis techniques are applied to user generated content (UGC) in social media comments (Facebook, Twitter and TripAdvisor) to identify these enablers and barriers. This analysis provides a set of explanatory variables that are combined with data from official statistics and the PBS observatory in Spain. As a result, a statistical model that assesses the connection between PBS use and certain characteristics of the PBS systems, utilizing sociodemographic, climate, and positive and negative opinion data extracted from social media is developed. The outcomes of the research work show that the identification of the main enablers and barriers of PBS systems can be effectively achieved following the research method and tools presented in the paper. The findings of the research can contribute to transportation planners to uncover the main factors related to the adoption and use of PBS systems, by taking advantage of publicly available data sources. Public bicycle observatory in Spain by given support. Document type: Article