Microtargeting and Electorate Segmentation: Data Mining the American National Election Studies

Murray, Gregg R.; Scime, Anthony

doi:10.1080/15377857.2010.497732

Cited by 37 publications

(22 citation statements)

References 22 publications

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“…A comunicação das campanhas 2.0 pode também ser mais individualizada, no sentido em que, devido às potencialidades da rede, o candidato tem a possibilidade de conhecer melhor o(s) seu(s) público(s)-alvo, adaptando a sua mensagem e tornando-a mais eficaz, numa técnica conhecida pelos especialistas como microtargeting (Harfoush, 2009). O microtargeting envolve a recolha e posterior utilização de dados recolhidos sobre os eleitores em grandes bases de dados que segmentam os potenciais eleitores por características sociodemográficas, envolvimento e posicionamento político, questões sociais e económicas, etc., permitindo a elaboração de mensagens específicas e de cariz personalizado (Murray e Scime, 2010).…”

Section: Quadrounclassified

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Eleições autárquicas 2.0: análise das estratégias de comunicação online de candidatos, partidos e movimentos independentes

Santos

Bicho

2016

SPP

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Resumo As redes sociais são uma ferramenta indispensável na comunicação política em período de campanha eleitoral. Este artigo pretende contribuir para o debate teórico sobre se as campanhas online contribuem para uma mudança de paradigma comunicacional entre candidatos e eleitores ou, ao invés, reproduzem os estilos e formatos preconizados pelos mass media. O estudo parte da análise de conteúdo das páginas de Facebook de partidos políticos e movimentos independentes relativas às eleições autárquicas de setembro de 2013. Após a análise descritiva é apresentado um modelo explicativo exploratório sobre as variações na interatividade entre páginas.Palavras-chave redes sociais, eleições, comunicação política, campanha eleitoral. AbstractThe social networks are an indispensable tool for political communication during election campaigns. This article seeks to contribute to the theoretical on whether online campaigns are helping change the paradigm for communication between candidates and voters, or whether on the contrary they are reproducing the styles and formats put forward by the mass media. The study begins by analysing the content of the Facebook pages of political parties and independent movements regarding the September 2013 local elections. The authors then present an exploratory model that seeks to explain the variations in interactivity from one page to another.

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Section: Quadrounclassified

“…Esta foi a técnica que muitos afirmam ter feito com que Obama ganhasse as eleições presidenciais nos Estados Unidos em 2008 (Murray e Scime, 2010). As redes sociais encerram uma imensa possibilidade ao nível da exploração desta técnica que foi subutilizada na campanha eleitoral em análise.…”

Section: Quadrounclassified

Eleições autárquicas 2.0: análise das estratégias de comunicação online de candidatos, partidos e movimentos independentes

Santos

Bicho

2016

SPP

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“…To our knowledge, there has only been little work on this topic in the literature, some notable exceptions including Wielhouwer (2003); Parry, Barth, Kropf, and Jones (2008) or Murray and Scime (2010). Identifying the right people to target is important because it reduces wasteful spending (e.g., targeting a person who is very unlikely, or not even eligible, to vote would be considered extremely wasteful) and allows campaigns to efficiently allocate their limited resources.…”

Section: Campaigning Mobilization and Turnout In The United Statesmentioning

confidence: 99%

“…For instance, Malchow (2008) promotes a linear probability model as well as tree-like models such as CHAID (Kass 1980) for political microtargeting. Murray and Scime (2010) suggest decision trees as well. Other state-of-the-art approaches that are used include logistic or probit regression.…”

Section: How Is Targeting Carried Out?mentioning

confidence: 99%

Influencing Elections with Statistics: Targeting Voters with Logistic Regression Trees

Rusch

Lee²,

Hornik

et al. 2012

SSRN Journal

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Political campaigning has become a multi-million dollar business. A substantial proportion of a campaign's budget is spent on voter mobilization, i.e., on identifying and influencing as many people as possible to vote. Based on data, campaigns use statistical tools to provide a basis for deciding who to target. While the data available is usually rich, campaigns have traditionally relied on a rather limited selection of information, often including only previous voting behavior and one or two demographical variables. Statistical procedures that are currently in use include logistic regression or standard classification tree methods like CHAID, but there is a growing interest in employing modern data mining approaches. Along the lines of this development, we propose a modern framework for voter targeting called LORET (for logistic regression trees) that employs trees (with possibly just a single root node) containing logistic regressions (with possibly just an intercept) in every leaf. Thus, they contain logistic regression and classification trees as special cases and allow for a synthesis of both techniques under one umbrella. We explore various flavors of LORET models that (a) compare the effect of using the full set of available variables against using only limited information and (b) investigate their varying effects either as regressors in the logistic model components or as partitioning variables in the tree components. To assess model performance and illustrate targeting, we apply LORET to a data set of 19,634 eligible voters from the 2004 US presidential election. We find that augmenting the standard set of variables (such as age and voting history) together with additional predictor variables (such as the household composition in terms of party affiliation and each individual's rank in the household) clearly improves predictive accuracy. We also find that LORET models based on tree induction outbeat the unpartitioned competitors. Additionally, LORET models using both partitioning variables and regressors in the resulting nodes can improve the efficiency of allocating campaign resources while still providing intelligible models.

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“…There is also evidence of data mining taking place through what could essentially be termed a decision support system (Jackson, 2005b) . The aim of data mining seems to be to identity segments that can be targeted with customised marketing messages via direct marketing techniques (D'Auria Stanton, 2006;Drew et al, 2001;Murray & Scime, 2010;Peltier & Schribrowsky, 1997;Samli et al, 2002;Vasanen & Raulas, 2006).…”

Section: Data Management and Market Orientationmentioning

confidence: 99%

Local Political Marketing in the Context of the Conservative Party

Reeves

2013

Journal of Nonprofit & Public Sector Marketing

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Microtargeting and Electorate Segmentation: Data Mining the American National Election Studies

Cited by 37 publications

References 22 publications

Eleições autárquicas 2.0: análise das estratégias de comunicação online de candidatos, partidos e movimentos independentes

Eleições autárquicas 2.0: análise das estratégias de comunicação online de candidatos, partidos e movimentos independentes

Influencing Elections with Statistics: Targeting Voters with Logistic Regression Trees

Local Political Marketing in the Context of the Conservative Party

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