How efficient is Twitter: Predicting 2012 U.S. presidential elections using Support Vector Machine via Twitter and comparing against Iowa Electronic Markets

Attarwala, Abbas; Dimitrov, Stanko; Obeidi, Amer

doi:10.1109/intellisys.2017.8324363

Cited by 17 publications

(7 citation statements)

References 20 publications

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“…Soler [4] developed a tool to define experiments and to capture the defined conversations and have applied it to the cases of three Spanish elections during 2011 and 2012. Soler concludes that Twitter may be a valid tool for predicting election result, confirm several aforementioned researches such as [9,12].…”

Section: Related Worksupporting

confidence: 71%

“…A total of 40 million unique tweets were collected and analyzed between September 29th, 2012 and November 6th, 2012. The SVM prediction results are positively correlated with the IEM and predict Obama winning the election, implying that Twitter can be considered as a valid source in predicting US Presidential election outcomes [9]. Huyen et al used the United States election in 2016 as the source data from Twitter.…”

Section: Related Workmentioning

confidence: 99%

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Prediction and analysis of Indonesia Presidential election from Twitter using sentiment analysis

2018

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Elections in Indonesia have taken place since 1955 to elect a legislature. At a national level, Indonesian people did not elect a president until 2004. For the first time, the president, and members of People's Consultative Assembly will be elected on the same day [1]. The next general election that will be held in Indonesia is next year on 17 April 2019. Related to this situation, discussion and prediction about who is the Presidential candidate in Indonesia become a hot and interesting conversation among Indonesian citizen, and many of them expressed it through social media. Election-related hashtags are some of the most used hashtags among Indonesian netizens, most of them is a form of support to Jokowi and Prabowo, such as #PilihPrabowo (vote for Prabowo) and #AkhirnyaMili-hJokowi (finally vote for Jokowi) [2]. Political campaigns have exploited this vast array of information available on the above platforms to draw insights about user opinions and thus design their campaign strategy. Huge investments by politicians in social media campaigns right before an election along with arguments and debates between their supporters and opponents only enhance the claim that views and opinions posted by users have a bearing on the results of an election [3]. On the other way, the information

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Section: Related Worksupporting

confidence: 71%

Section: Related Workmentioning

confidence: 99%

Prediction and analysis of Indonesia Presidential election from Twitter using sentiment analysis

2018

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“…In the virtual campaign using Twitter, we found that the conversations that were circulating were very much dominated by SARA narratives, where each camp used it to attack each other [22]. The battle of SARA, based propaganda testimonials is visible in both accounts [23]. The @Pababowo account in the campaign also once said thanks to the scholars who support it, which is a type of testimonial propaganda [24].…”

Section: Intertextualitymentioning

confidence: 99%

The Battle of SARA Politicization as a Threat to Virtual Public Spaces and Indonesian Cyber- Democracy (Semiotics Analysis on 2019 Presidential Election Campaign Narrative on Twitter between The Incumbent and The Opposite)

Kadju¹,

Gusfa²

2021

Proceedings of the 1st MICOSS Mercu Buana International Conference on Social Sciences, MICOSS 2020, September 28-29, 2020, Jaka

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Currently Indonesia is slowly starting to enter the era of community 5.0 or also called integrative virtual community created by the help of big data technology. This phenomenon then affects all aspects of Indonesian people's lives, such as social, economic, cultural, and so on. Even virtual reality continues to expand in the lives of Indonesian people, because the development of new media makes the political domain come to switch to cyberspace. Not a few social media accounts are used as buzzers, both for upgrading coalition, or downgrading the political opponents. This is very visible in the campaign of the 2019 Presidential Election in Indonesia. That is why this research uses a critical paradigm with Critical Discourse Analysis (CDA) from Teun van Dijk to analyze the narratives of the political campaign at the 2019 Presidential Election critically concerning the construction of Indonesian democracy. As a theoretical basis, the author combines the concept of Lebenswelt by Jürgen Habermas and Zwischenraum by Hannah Arendt to develop the meaning of democracy participatory-substantive, which in practice today tends to put more priority on procedural aspects. The results showed that both the incumbent stronghold (Joko Widodo and Ma'ruf Amin), as well as the opposition (Prabowo Subianto and Sandiaga Uno) both use social media to amplify their political campaigns respectively. However, many supporting accounts from each faction actually use attacking campaigns in the form of propaganda, provocation, SARA, and Hoax. Each camp only focuses on mere procedural aspects with the aim to win, without providing good political education and democracy for the people of Indonesia. This then makes Indonesian democracy a thick style plurality, tolerance, and Unity in Diversity actually began to fade. In short, the narratives that were built during the 2019 Presidential Election campaign on Twitter made the public partly divided and certainly greatly threatens substantive democracy in Indonesia.

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“…Several papers (Attarwala et al, 2017;Dionísio et al, 2019;Le Sceller et al, 2017) introduced Twitter-based approaches to design a pipeline for threat detection and, more generally, semantic analysis. Dionísio et al (2019) start from a set of customers, whose experts chose the Twitter cybersecurity accounts to monitor.…”

Section: Real-time Threat Identificationmentioning

confidence: 99%

Interpretable Identification of Cybersecurity Vulnerabilities from News Articles

Foret¹,

Ruşeţi

Sandescu

et al. 2021

Proceedings of the Conference Recent Advances in Natural Language Processing - Deep Learning for Natural Language Processing Me

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How efficient is Twitter: Predicting 2012 U.S. presidential elections using Support Vector Machine via Twitter and comparing against Iowa Electronic Markets

Cited by 17 publications

References 20 publications

Prediction and analysis of Indonesia Presidential election from Twitter using sentiment analysis

Prediction and analysis of Indonesia Presidential election from Twitter using sentiment analysis

The Battle of SARA Politicization as a Threat to Virtual Public Spaces and Indonesian Cyber- Democracy (Semiotics Analysis on 2019 Presidential Election Campaign Narrative on Twitter between The Incumbent and The Opposite)

Interpretable Identification of Cybersecurity Vulnerabilities from News Articles

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