Mediatisation in Twitter: an exploratory analysis of the 2015 Spanish general election

Baviera, Tomás; Calvo, Dafne; Abad, Germán Llorca

doi:10.1080/13216597.2019.1634619

Cited by 12 publications

(9 citation statements)

References 73 publications

(70 reference statements)

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“…• Analysis of the political representativeness of Twitter users [3] • Real-time Twitter analysis [4][5][6] • Democratic elections [7][8][9][10][11][12][13] • The uses of Twitter by populists [14] • Misinformation dissemination and event detection in social networks [15][16][17] • Online public shaming [18] • and many more Furthermore, there exist plenty of public available datasets. E.g., a curated collection [19] is hosted on Zenodo [20] and covers several datasets of political campaigns [8,9], online misinformation networks [21], event detection in temporal networks [22], public shaming [23], Twitter-related word vectors [24], retweeting timeseries [25], and even continuously updated samples of a nations-wide Twitter usage [26].…”

Section: Introductionmentioning

confidence: 99%

Redundancy Reduction in Twitter Event Streams

Kratzke¹

2020

Preprint

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The data from social networks like Twitter is a valuable source for research but full of redundancy, making it hard to provide large-scale, self-contained, and small datasets. The data recording is a common problem in social media-based studies and could be standardized. Sadly, this is hardly done. This paper reports on lessons learned from a long-term evaluation study recording the complete public sample of the German and English Twitter stream. It presents a recording solution proposal that merely chunks a linear stream of events to reduce redundancy. If events are observed multiple times within the time-span of a chunk, only the latest observation is written to the chunk. A 10 Gigabyte Twitter raw dataset covering 1,2 Million Tweets of 120.000 users recorded between June and September 2017 was used to analyze expectable compression rates. It turned out that resulting datasets need only between 10\% and 20\% of the original data size without losing any event, metadata or the relationships between single events. This kind of redundancy reduction recording makes it possible to curate large-scale (even nation-wide), self-contained, and small datasets of social networks for research in a standardized and reproducible manner.

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Section: Introductionmentioning

confidence: 99%

Redundancy Reduction in Twitter Event Streams

Kratzke¹

2020

Preprint

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“…En cualquier caso, las redes sociales forman parte inseparable de la comunicación política actual, ya que ningún político acudiría a un proceso electoral sin considerarlas cuidadosamente(Davis, Bacha y Just, 2016).En el panorama mediático actual, la comunicación política forma parte indisoluble de los discursos informativos, pero también de los del docudrama o incluso los ficcionales, creando un espacio público que es interdependiente de los medios de comunicación. De esta forma, la comunicación política está estructurada por herramientas mediáticas concretas que forman parte de la esfera pública, por lo que los medios de comunicación son esenciales para difundir información sobre noticias políticas(Baviera, T., Calvo, D., & Llorca-Abad, G. 2019). Y entre ellos y con creciente influencia, las redes sociales forman parte inseparable de la comunicación política actual y a la vez son el motor imprescindible de esa mediatización de la política actual.…”

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Presencia e interacción de los candidatos a la presidencia del Gobierno de España en las principales redes sociales durante la campaña electoral de noviembre de 2019

Díaz

Olmo²

2021

Revista OBETS

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La comunicación política de los candidatos electorales en las redes sociales de forma autónoma o en coordinación con la comunicación del partido, resulta cada vez más definitoria en los resultados de los procesos electorales. El presente trabajo analiza esa presencia de los candidatos a la presidencia del Gobierno de España en Twitter y Facebook durante la campaña electoral previa a las pasadas elecciones del 10 de noviembre de 2019. Busca valorar y comprender cómo en un contexto político de bloqueo, resulta necesario estudiar la importancia de las interacciones del candidato; así este texto se centra en el análisis de los perfiles en estas redes sociales de los candidatos. Utilizando una metodología cuantitativa y mediante el empleo de herramientas como Fanpage Karma y Social Analytics, este estudio lleva a cabo un análisis de caso comparado de los candidatos de los principales partidos en redes. Los resultados nos permiten conocer cómo los líderes políticos españoles emplean las redes sociales, al mismo tiempo se muestra y analiza la relación entre la interacción del candidato y sus resultados electorales.

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“…Moreover, it had the benefit of evaluating how specific resources and techniques perform in different languages. As a result of this work, a new dataset of political tweets was curated, proving very useful for new lines of research in political theories (Baviera, Calvo, and Llorca-Abad, 2019). The objective of this task was to classify the topic discussed in a political text from social media.…”

Section: Discussionmentioning

confidence: 99%

“…A subsample of 4.000 tweets was randomly extracted and labelled separately by each of the three coders. The complete details of this annotation process can be found in the work of Baviera, Calvo, and Llorca-Abad, 2019.…”

Section: Evaluation Frameworkmentioning

confidence: 99%

Natural Language Processing using Deep Learning in Social Media

Fayos¹,

Teresa²

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In the last years, Deep Learning (DL) has revolutionised the potential of automatic systems that handle Natural Language Processing (NLP) tasks. We have witnessed a tremendous advance in the performance of these systems. Nowadays, we found embedded systems ubiquitously, determining the intent of the text we write, the sentiment of our tweets or our political views, for citing some examples.In this thesis, we proposed several NLP models for addressing tasks that deal with social media text. Concretely, this work is focused mainly on Sentiment Analysis and Personality Recognition tasks. Sentiment Analysis is one of the leading problems in NLP, consists of determining the polarity of a text, and it is a well-known task where the number of resources and models proposed is vast. In contrast, Personality Recognition is a breakthrough task that aims to determine the users' personality using their writing style, but it is more a niche task with fewer resources designed ad-hoc but with great potential.Despite the fact that the principal focus of this work was on the development of Deep Learning models, we have also proposed models based on linguistic resources and classical Machine Learning models. Moreover, in this more straightforward setup, we have explored the nuances of different language devices, such as the impact of emotions in the correct classification of the sentiment expressed in a text.Afterwards, DL models were developed, particularly Convolutional Neural Networks (CNNs), to address previously described tasks. In the case of Personality v • S'ha desenvolupat un marc teòric que permet interpretar xarxes neuronals convolucionals.

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Mediatisation in Twitter: an exploratory analysis of the 2015 Spanish general election

Cited by 12 publications

References 73 publications

Redundancy Reduction in Twitter Event Streams

Redundancy Reduction in Twitter Event Streams

Presencia e interacción de los candidatos a la presidencia del Gobierno de España en las principales redes sociales durante la campaña electoral de noviembre de 2019

Natural Language Processing using Deep Learning in Social Media

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