The role of bot squads in the political propaganda on Twitter

Caldarelli, Guido; Nicola, Rocco De; Vigna, Fabio Del; Petrocchi, Marinella; Saracco, Fabio

doi:10.1038/s42005-020-0340-4

Cited by 96 publications

(117 citation statements)

References 70 publications

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“…Sin embargo, el alcance de las métricas de engagement debe ser interpretado cautelosamente, en tanto se han extendido estrategias automatizadas para manipular difusión y algoritmos (Arnaudo, 2017), mediante la compra de seguidores, likes o comparticiones (p. ej., Fernández, 2018;Caldarelli et al, 2019;Carrasco, 2019). El engagement manifestado en redes sociales sería así una combinación de las interacciones de usuarios reales y computerizados.…”

Section: Discusión Y Conclusionesunclassified

Batalla de frames en la campaña electoral de abril de 2019. Engagement y promoción de mensajes de los partidos políticos en Facebook

Ballesteros

Gómez-García

2020

EPI

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Framing processes are one of the preferred objects of study in the area of Communication, despite the frequent criticism regarding their theoretical and methodological strength. This study follows the proposal of Matthes and Kohring (2008) of the detection of frames through statistical analysis of clusters that operationalize the components as defined by Entman (2003) using framing elements. This is applied to the study of the electoral campaign on Facebook of the main Spanish political parties in the election of 28 April 2019. All messages published on this social network during the 15 days of the electoral campaign were captured automatically. The use of four large frames by the parties was detected, corresponding to events and political questions, request for vote, the rival party, and media treatment. The parties used these frames to different degrees: from the institutional and positive campaign of the PSOE, to the campaign aimed at criticizing the ruling party of the main opposition party, the PP, through the inclination towards media treatment of Unidas Podemos, or a focus on their own events and proposals by Ciudadanos and Vox. A negative correlation was detected between the frames most used by the political formations as a whole and the level of user engagement on Facebook, although the use of frames by PSOE and Unidas Podemos showed a greater parallelism with the levels of interaction in this social network. Resumen Los procesos de enmarcado, encuadre o framing son uno de los objetos de estudio preferentes en el área de Comunicación, a pesar de las frecuentes y reputadas críticas sobre su solidez teórica y metodológica. En esta investigación se sigue la propuesta de Matthes y Kohring (2008) para la detección de frames mediante análisis estadístico de conglomerados que operacionaliza en elementos de enmarcado los componentes de la definición de Entman (1993). Se aplica al estudio de la campaña electoral que hicieron los principales partidos políticos españoles a través de Facebook en la convocatoria del 28 de abril de 2019. Se capturaron automatizadamente todos los mensajes publicados en esta red social en los quince días de campaña electoral, detectándose el uso de cuatro grandes frames por parte de los partidos: marco de eventos y cuestiones políticas, marco de petición de voto, marco del partido rival y marco del tratamiento mediático. Los partidos utilizaron en diferente medida estos marcos: desde la campaña institucional y en positivo del PSOE; a la campaña volcada en criticar al partido gobernante del principal partido de la oposición, el PP; pasando por la inclinación hacia el tratamiento mediático de Unidas Podemos, o a centrarse en sus propios actos y propuestas de Ciudadanos y Vox. Se detectó una correlación negativa entre los frames más empleados por las formaciones políticas en su conjunto y el nivel de engagement en Facebook, si bien la utilización concreta de los marcos por parte del PSOE y Unidas Podemos sí mostró cierto paralelismo con los niveles de interacción en esta red social.

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Section: Discusión Y Conclusionesunclassified

Batalla de frames en la campaña electoral de abril de 2019. Engagement y promoción de mensajes de los partidos políticos en Facebook

Ballesteros

Gómez-García

2020

EPI

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“…Indeed, several platforms have been the subject of polarization studies, from Twitter, to YouTube, to Facebook [4][5][6][7]. On Twitter, in particular, political polarization can be exacerbated by social bots that amplify divisive messages [8]. Polarized issues fall not only along ideological fault-lines [4], but can also touch on any collectively resonant topic [9].…”

Section: Introductionmentioning

confidence: 99%

No echo in the chambers of political interactions on Reddit

Morales

Monti

Starnini

2021

Sci Rep

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Echo chambers in online social networks, whereby users’ beliefs are reinforced by interactions with like-minded peers and insulation from others’ points of view, have been decried as a cause of political polarization. Here, we investigate their role in the debate around the 2016 US elections on Reddit, a fundamental platform for the success of Donald Trump. We identify Trump vs Clinton supporters and reconstruct their political interaction network. We observe a preference for cross-cutting political interactions between the two communities rather than within-group interactions, thus contradicting the echo chamber narrative. Furthermore, these interactions are asymmetrical: Clinton supporters are particularly eager to answer comments by Trump supporters. Beside asymmetric heterophily, users show assortative behavior for activity, and disassortative, asymmetric behavior for popularity. Our findings are tested against a null model of random interactions, by using two different approaches: a network rewiring which preserves the activity of nodes, and a logit regression which takes into account possible confounding factors. Finally, we explore possible socio-demographic implications. Users show a tendency for geographical homophily and a small positive correlation between cross-interactions and voter abstention. Our findings shed light on public opinion formation on social media, calling for a better understanding of the social dynamics at play in this context.

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“…Data were collected through the Filter API since 23rd of January to 22nd of February 2019 and targeted the Italian debate on migration. Data were previously analysed in [ 16 ]. In the dataset, the information about the nature, automated or not (BOT or not), of the users is present.…”

Section: Resultsmentioning

confidence: 99%

“…In the dataset, the information about the nature, automated or not (BOT or not), of the users is present. The BOT detection algorithm embedded is a lightweight version of the classifier proposed in [ 10 ]; more details on the dataset can be found in [ 16 ].…”

Section: Resultsmentioning

confidence: 99%

“…Nowadays, such intermediation is not present anymore: every blog or account on Facebook or Twitter assumes truthfulness just for existing online [ 3 – 6 ]. Due to this abrupt change of paradigm in the fruition of news, we observe a great increase of the diffusion of misinformation [ 7 – 9 ], that appears on the web via the use of automated [ 10 – 16 ] or genuine accounts [ 4 , 16 – 20 ]. It has been observed that the diffusion of disinformation or misinformation campaigns leans on the emotionality of users [ 3 , 4 , 6 , 21 ].…”

Section: Introductionmentioning

confidence: 99%

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A model for the Twitter sentiment curve

2021

Self Cite

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Twitter is among the most used online platforms for the political communications, due to the concision of its messages (which is particularly suitable for political slogans) and the quick diffusion of messages. Especially when the argument stimulate the emotionality of users, the content on Twitter is shared with extreme speed and thus studying the tweet sentiment if of utmost importance to predict the evolution of the discussions and the register of the relative narratives. In this article, we present a model able to reproduce the dynamics of the sentiments of tweets related to specific topics and periods and to provide a prediction of the sentiment of the future posts based on the observed past. The model is a recent variant of the Pólya urn, introduced and studied in Aletti and Crimaldi (2019, 2020), which is characterized by a “local” reinforcement, i.e. a reinforcement mechanism mainly based on the most recent observations, and by a random persistent fluctuation of the predictive mean. In particular, this latter feature is capable of capturing the trend fluctuations in the sentiment curve. While the proposed model is extremely general and may be also employed in other contexts, it has been tested on several Twitter data sets and demonstrated greater performances compared to the standard Pólya urn model. Moreover, the different performances on different data sets highlight different emotional sensitivities respect to a public event.

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The role of bot squads in the political propaganda on Twitter

Cited by 96 publications

References 70 publications

Batalla de frames en la campaña electoral de abril de 2019. Engagement y promoción de mensajes de los partidos políticos en Facebook

Batalla de frames en la campaña electoral de abril de 2019. Engagement y promoción de mensajes de los partidos políticos en Facebook

No echo in the chambers of political interactions on Reddit

A model for the Twitter sentiment curve

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