Election campaigning on social media: Politicians, audiences and the mediation of political communication on Facebook and Twitter

Stier, Sebastian; Bleier, Arnim; Lietz, Haiko; Strohmaier, Markus

doi:10.31235/osf.io/58u4c

Cited by 5 publications

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“…Among the classical clustering algorithms, Gibbs Sampling algorithm for the Dirichlet Multinomial Mixture model (GSDMM), K-means and the Spherical algorithms are widely used. GSDMM is useful for dealing with tweets and used by several studies [37][38][39][40]. Different variations of K-means and Spherical Kmeans were also used for rare disease analysis [41].…”

Section: Introductionmentioning

confidence: 99%

An Exploratory Study of Social Media Analysis for Rare Diseases Using Machine Learning Algorithms: A Case Study of Trigeminal Neuralgia

Mombini¹,

Li²,

Zhang³

et al. 2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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Rare diseases, affecting approximately 30 million Americans, are often poorly understood by clinicians due to lack of familiarity with the disease and proper research. Patients with rare diseases are often unfavorably treated, especially those with extremely painful chronic orofacial rare disorders. In the absence of structured knowledge, such patients often choose social media to seek help from peers within patient-oriented social media communities thereby generating tremendous amounts of unstructured data daily. We investigate whether we can organize this unstructured data using machine learning to help members of rare communities find relevant information more efficiently in real-time. We chose Trigeminal Neuralgia (TN), an extremely painful rare disorder, as our case study and collected 20,000 social media TN posts. We categorized TN posts into Twitter (very short), and Facebook (short, medium, long) datasets based on message length and performed three clustering experiments. Results revealed GSDMM outperformed both K-means and Spherical K-means in clustering Facebook especially for short messages in terms of speed. For long messages, MDS reduction outperformed the PCA when both were used with K-means and Spherical K-means. Our study demonstrated the need for further topic modeling to utilize among high level clusters based on semantic analysis of posts within each cluster.

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Section: Introductionmentioning

confidence: 99%

An Exploratory Study of Social Media Analysis for Rare Diseases Using Machine Learning Algorithms: A Case Study of Trigeminal Neuralgia

Mombini¹,

Li²,

Zhang³

et al. 2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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Influencers and the Building of Political Brands—The Case of India

Sharma¹,

Jain²

2021

Political Branding in Turbulent Times

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Politicians on Social Media. The online database of members of national parliaments on Twitter

Haman

Školník

2021

EPI

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In this article, we present the new online database Politicians on Social Media (https://www.politiciansonsocialmedia.com), which is intended for both academics and the public. This database was created with the aim of being continuously updated and providing relevant information on politicians’ activity on social media. We first used data from this database to analyze Twitter. This social networking site is increasingly at the forefront of scientific interest due to its growing number of users. It is often examined with respect to how politicians use it. For politicians, Twitter is an opportunity not only to inform people about their activities but also to communicate directly with voters. Attention is focused on members of parliaments (MPs). We examine not only how many MPs have adopted Twitter but also how active they are on it. We also examine the determinants of Twitter adoption by MPs. We analyzed all countries of the European Union, the European Free Trade Association, and the United Kingdom. Therefore, the research includes 32 European countries. Our analysis revealed that most MPs have adopted Twitter in Western European countries such as France, Ireland, the Netherlands, Spain, or the United Kingdom, while MPs in Bulgaria, Hungary, Romania, and Slovakia use Twitter the least. Twitter is very actively used by Spanish and British MPs. By contrast, the least active MPs on Twitter are in post-communist countries such as Bulgaria and Romania. Our correlation analysis showed a strong association between the number of Twitter users in countries and the adoption of Twitter by MPs. Specifically, more Twitter users in a country correlates with its being adopted by more MPs.

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Election campaigning on social media: Politicians, audiences and the mediation of political communication on Facebook and Twitter

Cited by 5 publications

References 0 publications

An Exploratory Study of Social Media Analysis for Rare Diseases Using Machine Learning Algorithms: A Case Study of Trigeminal Neuralgia

An Exploratory Study of Social Media Analysis for Rare Diseases Using Machine Learning Algorithms: A Case Study of Trigeminal Neuralgia

Influencers and the Building of Political Brands—The Case of India

Politicians on Social Media. The online database of members of national parliaments on Twitter

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