When Politicians Talk About Politics: Identifying Political Tweets of Brazilian Congressmen

Oliveira, Lucas Santos de; Melo, Pedro O. S. Vaz de; Amaral, Marcelo Santos; Pinho, José Antônio Gomes de

doi:10.1609/icwsm.v12i1.15051

Cited by 7 publications

(4 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The BTM is a generative model for un-ordered word-pairs co-occurring within a document (e.g. a tweet) and has been proven effective in identifying topics in short texts (Jónsson and Stolee 2015;Oliveira et al 2018). Each IWT meme caption, whose length is short in general, is treated as document.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Understanding Visual Memes: An Empirical Analysis of Text Superimposed on Memes Shared on Twitter

Masood

Joseph

2020

ICWSM

View full text Add to dashboard Cite

Visual memes have become an important mechanism through which ideologically potent and hateful content spreads on today's social media platforms. At the same time, they are also a mechanism through which we convey much more mundane things, like pictures of cats with strange accents. Little is known, however, about the relative percentage of visual memes shared by real people that fall into these, or other, thematic categories. The present work focuses on visual memes that contain superimposed text. We carry out the first large-scale study on the themes contained in the text of these memes, which we refer to as image-with-text memes. We find that 30% of the image-with-text memes in our sample which have identifiable themes are politically relevant, and that these politically relevant memes are shared more often by Democrats than Republicans. We also find disparities in who expresses themselves via image-with-text memes, and images in general, versus other forms of expression on Twitter. The fact that some individuals use images with text to express themselves, instead of sending a plain text tweet, suggests potential consequences for the representativeness of analyses that ignore text contained in images.

show abstract

Section: Methodsmentioning

confidence: 99%

“…Note that we experimented with K = 30, 40 as well, and found that K = 20 had the highest level of coherence (Mimno et al 2011). Other parameters were selected according to previous work (Oliveira et al 2018).…”

Section: Methodsmentioning

confidence: 99%

Understanding Visual Memes: An Empirical Analysis of Text Superimposed on Memes Shared on Twitter

Masood

Joseph

2020

ICWSM

View full text Add to dashboard Cite

show abstract

“…Several studies have been conducted on the topic of parliamentarians and the adoption of social media or Internet technologies in Latin America, and these are primarily single case studies, for example, case studies on Brazil (Amaral;Pinho, 2017;Brandt;Vidotti, 2020;García-Sánchez et al, 2021;Miola, 2014a;2014b;Oliveira et al, 2018); Chile (Fuente-Alba-Cariola; Parada-Gavilán, 2019; Henríquez et al, 2022); or studies comparing Argentina, Paraguay, and Uruguay Marzuca, 2014;.…”

Section: Introductionmentioning

confidence: 99%

Political communication on social media in Latin America: unequal use of Twitter by members of parliament

Haman

2023

EPI

View full text Add to dashboard Cite

This article focuses on the under-researched topic of the use of Twitter by members of parliament (MPs) in Latin America. There have not yet been any thorough comparative studies on this topic, and the majority of publications on the region focus on single case studies. Previous studies have primarily concentrated on presidents, or in the case of MPs, on specific case studies. A total of 2,353,138 tweets were accessed via the Twitter API, and 3,215 MPs were examined. Regression models and correlations were used to answer research questions, and the main variables examined concerned individual characteristics of MPs (gender and age) and socioeconomic indicators of the country (number of people on Twitter, internet access, Human Development Index - HDI). As a result, this paper offers a report on how MPs in Latin America are currently utilizing Twitter. While his social network is used by more than 90% of MPs in some countries (Argentina, Colombia, Ecuador, El Salvador, Peru, and Uruguay), there are countries where fewer than half of MPs use it (Bolivia, Honduras, and Nicaragua). The results show that female MPs are more likely than male MPs to use Twitter. In addition, Twitter is being adopted more by younger MPs. Other results show that country characteristics such as internet penetration, Twitter population, and the HDI are significant predictors regarding the adoption and use of Twitter by MPs. These results are consistent with assumptions based on cost-benefit calculus. Thus, it does not make as much sense for politicians to adopt Twitter in countries where there are less people on Twitter and low internet penetration. In particular, if politicians want to be elected or inform citizens about their activities, they have an opportunity to reach voters through Twitter. However, this is only true if Twitter is used in their countries.

show abstract

“…Text-based embedding learning has been previously employed to understand phenomenon on social media (Alam, Joty, and Imran 2018;Chen, McKeever, and Delany 2019;Yan et al 2020;Bahgat, Wilson, and Magdy 2020), including politics on social media (Oliveira et al 2018;Hemphill and Schöpke-Gonzalez 2020). Some of the existing methods in the literature, which aim at embedding social media users based on the written content, concatenate all the posts of a user as a single document and then train a document level embedding model Pan 2017, 2018;Benton, Arora, and Dredze 2016) 1 .…”

Section: Introductionmentioning

confidence: 99%

American Politicians Diverge Systematically, Indian Politicians do so Chaotically: Text Embeddings as a Window into Party Polarization

Budhiraja¹,

Sharma²,

Agrawal³

et al. 2021

ICWSM

View full text Add to dashboard Cite

Conversations on polarization are increasingly central to discussions of politics and society, but the schisms between parties and states can be hard to identify systematically in what politicians say. In this paper, we demonstrate the use of representation learning as a window into political dialogue on social media through the tweets authored by politicians on Twitter. We propose to embed politicians in a space such that their output embedding vectors represent the content similarity between the two politicians based on their tweets. We further propose a short-text based embedding technique to overcome some of the shortcomings of the previous methods. The learnt embeddings for politicians of India and the United States show two trends. First, that in the US case, we find a clear distinction between Democrats and Republicans, which is also reflected in the coalescing of the states that lean towards each party placing likewise in a graphical space. However, in the Indian case, the federal structure, multiparty system, and linguistic differences clearly manifest in the coalescing political discourse in the largely monolingual north and the scattered regional states. Our work shows ways in which machine learning methods can offer a window into thinking about how polarized political discourses manifest in what politicians say online.

show abstract

When Politicians Talk About Politics: Identifying Political Tweets of Brazilian Congressmen

Cited by 7 publications

References 5 publications

Understanding Visual Memes: An Empirical Analysis of Text Superimposed on Memes Shared on Twitter

Understanding Visual Memes: An Empirical Analysis of Text Superimposed on Memes Shared on Twitter

Political communication on social media in Latin America: unequal use of Twitter by members of parliament

American Politicians Diverge Systematically, Indian Politicians do so Chaotically: Text Embeddings as a Window into Party Polarization

Contact Info

Product

Resources

About