Statistics, politics, and policy最新文献

{"title":"Predicting the Brexit Vote by Tracking and Classifying Public Opinion Using Twitter Data","authors":"Julio Amador Díaz López, Sofia Collignon-Delmar, K. Benoit, Akitaka Matsuo","doi":"10.1515/spp-2017-0006","DOIUrl":"https://doi.org/10.1515/spp-2017-0006","url":null,"abstract":"Abstract We use 23M Tweets related to the EU referendum in the UK to predict the Brexit vote. In particular, we use user-generated labels known as hashtags to build training sets related to the Leave/Remain campaign. Next, we train SVMs in order to classify Tweets. Finally, we compare our results to Internet and telephone polls. This approach not only allows to reduce the time of hand-coding data to create a training set, but also achieves high level of correlations with Internet polls. Our results suggest that Twitter data may be a suitable substitute for Internet polls and may be a useful complement for telephone polls. We also discuss the reach and limitations of this method.","PeriodicalId":90055,"journal":{"name":"Statistics, politics, and policy","volume":"1 1","pages":"104 - 85"},"PeriodicalIF":0.0,"publicationDate":"2017-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79946013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding the 2016 US Presidential Polls: The Importance of Hidden Trump Supporters","authors":"P. Enns, Julius Lagodny, Jonathon P. Schuldt","doi":"10.1515/spp-2017-0003","DOIUrl":"https://doi.org/10.1515/spp-2017-0003","url":null,"abstract":"Abstract Following Donald Trump’s unexpected victory in the 2016 US presidential election, the American Association for Public Opinion Research announced that “the polls clearly got it wrong” and noted that talk of a “crisis in polling” was already emerging. Although the national polls ended up being accurate, surveys just weeks before the election substantially over-stated Clinton’s lead and state polls showed systematic bias in favor of Clinton. Different explanations have been offered for these results, including non-response bias and late deciders. We argue, however, that these explanations cannot fully account for Trump’s underperformance in October surveys. Utilizing data from two national polls that we conducted in October of 2016 (n>2100 total) as well as 14 state-level polls from October, we find consistent evidence for the existence of “hidden” Trump supporters who were included in the surveys but did not openly express their intention to vote for Trump. Most notably, when we account for these hidden Trump supporters in our October survey data, both national and state-level analyses foreshadow Trump’s Election Day support. These results suggest that late-breaking campaign events may have had less influence than previously thought and the findings hold important implications for how scholars, media, and campaigns analyze future election surveys.","PeriodicalId":90055,"journal":{"name":"Statistics, politics, and policy","volume":"57 1","pages":"41 - 63"},"PeriodicalIF":0.0,"publicationDate":"2017-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87481142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Representativity of Election Polls","authors":"J. Bethlehem","doi":"10.1515/spp-2016-0002","DOIUrl":"https://doi.org/10.1515/spp-2016-0002","url":null,"abstract":"Abstract Election polls are conducted in many countries during election campaigns. Provided such polls are set up and carried out correctly, they can give an accurate indication of the voting intentions of people. However, the last couple of years these polls seem to be less able to predict election results. Examples are the polls for the general election in the UK of 2015, the Brexit referendum in the UK, and the presidential election in the US of 2016. The polls in the UK and the US have all in common that they are either telephone polls or online polls. It is shown in this paper that both type of polls suffer from lack of representativity. The compositions of their samples differ from that of the population. This can have several causes. For telephone polls, problems are mainly caused by increasing nonresponse rates, and lack of proper sampling frames. Most online polls are based on samples from web panels that are recruited by means of self-selection instead of random samples. Such web panels also not representative. The paper analyses the shortcomings of these election polls. The problems are illustrated by describing the polls in the UK and the US in some more detail.","PeriodicalId":90055,"journal":{"name":"Statistics, politics, and policy","volume":"219 1","pages":"1 - 12"},"PeriodicalIF":0.0,"publicationDate":"2017-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88074955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What do we Lose with Online-Only Surveys? Estimating the Bias in Selected Political Variables Due to Online Mode Restriction","authors":"Klaus Pforr, Tanja Dannwolf","doi":"10.1515/spp-2016-0004","DOIUrl":"https://doi.org/10.1515/spp-2016-0004","url":null,"abstract":"Abstract This paper adds to the discussion on the value of online surveys for political science research. Mainly because of the lower costs, collecting survey data over the web has become increasingly popular in recent years, despite the higher sampling and coverage error in web-only surveys, especially online access polls. Recruiting respondents for the actual panel surveys based on a representative sample using a different mode is regarded as a solution to the sampling problem. Two approaches have been used to tackle the problem of coverage error: Providing respondents with computers (e.g. LISS, ELIPPS, GIP) and offering a different mode than online to respondents, thereby adopting a mixed mode design (e.g. paper as in GALLUP, GESIS Panel). The literature suggests that offering participation in the respondent’s preferred mode affects response rates positively but not much is known about respondents’ reasoning to choose a specific mode. We argue that it is important to understand this decision to evaluate the selection into online surveys and the consequences this has for data quality. We investigate this question by drawing on data from the GESIS Panel face-to-face recruitment interview for building a mixed mode access panel (paper and web) in Germany that gave a mode choice to internet users. Our results suggest that web literacy, age and education alone do not explain the mode choice but that affinity towards the technology related to the online mode has an independent effect. In a second step, we analyse the effect of this selection mechanism on answers to questions on typical variables used in political participation research such as media competence, political interest and civic duty in the subsequent mixed mode survey. We assess the added value of adopting a mixed-mode strategy. The results inform the evaluation of biases in unimode online surveys.","PeriodicalId":90055,"journal":{"name":"Statistics, politics, and policy","volume":"21 1","pages":"105 - 120"},"PeriodicalIF":0.0,"publicationDate":"2017-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91307765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Voting in Nigeria: Determinants of Turnout in the 2015 Presidential Election","authors":"Cletus Famous Nwankwo, Uchenna Paulinus Okafor","doi":"10.1515/spp-2017-0010","DOIUrl":"https://doi.org/10.1515/spp-2017-0010","url":null,"abstract":"Abstract This paper investigates the determinants of voter turnout in the 2015 election in Nigeria. Variables drawn from political participation models were tested on the likelihood that they influence turnout. The paper finds that political trust and home ownership had a significant impact on participation more than other factors. However, it did not underestimate the influence socio-economic variables can have on voter turnout especially how they can sway the effect of political trust on individuals’ decision to turnout.","PeriodicalId":90055,"journal":{"name":"Statistics, politics, and policy","volume":"9 1","pages":"249 - 260"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79989943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editor’s Note","authors":"U. Wagschal","doi":"10.1515/spp-2018-0002","DOIUrl":"https://doi.org/10.1515/spp-2018-0002","url":null,"abstract":"The application of big data in law, social and political sciences is still in its infancy. However big data analysis is not anymore a fancy thing, but has reached all social science disciplines. Despite the fact that governments, social media and private digital data sources have begun to produce huge amounts of accessible data, interpretation and analysis of these data streams still constitutes a technical and functional challenge. And even in the neighboring fields of economics, econometrics and finance – disciplines longer accustomed to huge amounts of real-time data for example in stock market analysis – the applications of big data frameworks for huge-n and automatically generated information are still considered uncommon and innovative. Regarding most research questions in all of these fields either a suitable and structured data foundation or a researcher equipped with profound knowledge and suitable skills for big data analysis is missing. Statistics, Politics and Policy called for outstanding contributions related to Big Data Analysis. The principle aim is to promote research in this specific domain of data research. By selecting and subsequently publishing the following contributions we intent to demonstrate the potential and the adaptability of big data research for all involved disciplines and share interesting new possibilities to apply these techniques with the scientific community. The first contribution of our segment on big data is concerned with a big data framework in education, laying the theoretical foundations for the use of big data in educational settings. The second contribution is presenting a new, semi-automated approach in retrieving Twitter information. The third paper is concerned with textual data analysis based on parliamentary oversight hearings. The forth contribution is concerned with the language of dissenting opinion in Supreme Court cases. All contributions advance the usage and accessibility of automated data research in the concerning fields and improve our understanding of the related research questions. After our special segment on big data we decided to further include two contributions related to the political subfields of voting and policy in the current","PeriodicalId":90055,"journal":{"name":"Statistics, politics, and policy","volume":"98 1","pages":"121 - 122"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85833345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Demographic Peace? Youth Bulges and Other Population-Related Causes of Domestic Conflict","authors":"Uwe Wagschal, Thomas Metz","doi":"10.1515/spp-2017-0004","DOIUrl":"https://doi.org/10.1515/spp-2017-0004","url":null,"abstract":"Abstract The following article analyzes violent political conflicts. Starting from theoretical debates on the determinants of violent conflicts, it focuses on intrastate conflicts. The main explanatory factors which are analyzed from different perspectives are demographic factors. Not only the size of the population or the population density is relevant, but also the so-called youth bulge. Youth bulges, i.e. large cohorts of young people, are the main driving forces of war. Especially variants like male youth bulges are highly significant in the empirical analysis. The article uses different data sets for the analysis, like the Global Peace Index and the CONIS data. Various statistical methods are used in the analysis. The article also draws attention to intervening factors, which might intensify or lessen the impact of the youth bulge.","PeriodicalId":90055,"journal":{"name":"Statistics, politics, and policy","volume":"86 1","pages":"55 - 97"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74619568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Self-Interest or Solidarity?","authors":"S. Mueller, A. Vatter, C. Schmid","doi":"10.1515/spp-2016-0003","DOIUrl":"https://doi.org/10.1515/spp-2016-0003","url":null,"abstract":"Abstract This article puts the self-interest hypothesis to an empirical test by analysing the 2004 referendum on fiscal equalisation in Switzerland. That vote put forth a series of reforms which created regional winners and loser in terms of having to pay or receiving unconditional funding. Although Switzerland is usually portrayed as a paradigmatic case in terms of inter-regional solidarity and national integration, we show that rational and selfish cost-benefit calculations strongly mattered for the end-result. We rely on a multi-level model with referendum and other data on more than 2700 municipalities and all 26 cantons. More broadly, our findings confirm that rational choice theory works well for voting on straightforward monetary issues with a clearly defined group of winners and losers. However, symbolic interests such as party strength and cultural predispositions against state intervention and in favour of subsidiarity also matter and need to be taken into account alongside.","PeriodicalId":90055,"journal":{"name":"Statistics, politics, and policy","volume":"2 1","pages":"3 - 28"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87372793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Measurement Error and Attenuation Bias in Exponential Random Graph Models","authors":"Yeaji Kim, Leonardo Antenangeli, J. Kirkland","doi":"10.1515/spp-2016-0001","DOIUrl":"https://doi.org/10.1515/spp-2016-0001","url":null,"abstract":"Abstract Exponential Random Graph Models (ERGMs) are becoming increasingly popular tools for estimating the properties of social networks across the social sciences. While the asymptotic properties of ERGMs are well understood, much less is known about how ERGMs perform in the face of violations of the assumptions that drive those asymptotic properties. Given that empirical social networks rarely meet the strenuous assumptions of the ERGM perfectly, practical researchers are often in the position of knowing their coefficients are imperfect, but not knowing precisely how wrong those coefficients may be. In this research, we examine one violation of the asymptotic assumptions of ERGMs – perfectly measured social networks. Using several Monte Carlo simulations, we demonstrate that even randomly distributed measurement errors in networks under study can cause considerable attenuation in coefficients from ERGMs, and do real harm to subsequent hypothesis tests.","PeriodicalId":90055,"journal":{"name":"Statistics, politics, and policy","volume":"44 1","pages":"29 - 54"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86760341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editor’s Note","authors":"U. Wagschal","doi":"10.1515/spp-2017-0008","DOIUrl":"https://doi.org/10.1515/spp-2017-0008","url":null,"abstract":"This is the first edition since I took over the position as Editor-in-Chief of Statistics, Politics and Policy (SPP) from my dear colleague Joel Middleton (Professor at University of California, Berkeley). I would like to thank Joel for his hard work and endeavours in the past. Several things have changed for SPP. First, a new editorial board was established. The new board now consists of 12 editors from 10 countries and 3 continents. The board members are representatives of a broad range of perspectives: Leading experts on statistics and methodology, as well as on policy analysis and politics. Second, the review process of our journal has improved considerably. We changed from a simple double review process to a double blind peer-review process. Our intention is to fully adopt all established international standards. We also improved the review process in many ways. Reviewers can now use the ScholarOne based platform to efficiently review and evaluate their corresponding articles. Different aspects of a contributed paper can be rated with scores of 1–5 and comments for improvements can be included in a flexible way to make the process of evaluation neat and faster. Assessing the quality of a paper thus has become much clearer and much more efficient. Third, the scope of the journal will also be slightly adjusted. Statistics, Politics and Policy studies the ways that statistical analysis drives public policy decisions, and publishes significant research on the application of statistical ideas to problems that relate to policy implementation. In comparison to the past, when the majority of articles addressed statistical problems and methodology, we are more interested in statistical applications and policy analysis. Fourth, from this year on we will award a prize for the best contribution in the SPP. The editorial board will decide to which author the price is given. With all these changes in place SPP is on course to release two major issues in 2017 regarding the following fields of interest: The upcoming issue 1 (Vol. 2017) of SPP will focus on the quality of polls and surveys. Recently, polls and surveys struggled to predict accurately voter preferences in important elections worldwide. Our next issue will reflect on this","PeriodicalId":90055,"journal":{"name":"Statistics, politics, and policy","volume":"11 1","pages":"1 - 2"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80988247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}