The Community for Technology Leaders
RSS Icon
Issue No.12 - Dec. (2011 vol.17)
pp: 2384-2391
Jo Wood , giCentre, City University London
Donia Badawood , giCentre, City University London
Jason Dykes , giCentre, City University London
Aidan Slingsby , giCentre, City University London
The relationship between candidates' position on a ballot paper and vote rank is explored in the case of 5000 candidates for the UK 2010 local government elections in the Greater London area. This design study uses hierarchical spatially arranged graphics to represent two locations that affect candidates at very different scales: the geographical areas for which they seek election and the spatial location of their names on the ballot paper. This approach allows the effect of position bias to be assessed; that is, the degree to which the position of a candidate's name on the ballot paper influences the number of votes received by the candidate, and whether this varies geographically. Results show that position bias was significant enough to influence rank order of candidates, and in the case of many marginal electoral wards, to influence who was elected to government. Position bias was observed most strongly for Liberal Democrat candidates but present for all major political parties. Visual analysis of classification of candidate names by ethnicity suggests that this too had an effect on votes received by candidates, in some cases overcoming alphabetic name bias. The results found contradict some earlier research suggesting that alphabetic name bias was not sufficiently significant to affect electoral outcome and add new evidence for the geographic and ethnicity influences on voting behaviour. The visual approach proposed here can be applied to a wider range of electoral data and the patterns identified and hypotheses derived from them could have significant implications for the design of ballot papers and the conduct of fair elections.
Voting, election, bias, democracy, governance, treemaps, geovisualization, hierarchy, governance.
Jo Wood, Donia Badawood, Jason Dykes, Aidan Slingsby, "BallotMaps: Detecting Name Bias in Alphabetically Ordered Ballot Papers", IEEE Transactions on Visualization & Computer Graphics, vol.17, no. 12, pp. 2384-2391, Dec. 2011, doi:10.1109/TVCG.2011.174
[1] R. Darcy, Position effects with party column ballots. The Western Political Quarterly, 39 (4): 648–662, 1986.
[2] giCentre. Hierarchical data explorer. hide, 2011.
[3] GLA. Borough council election results. borough-council-election-results-2010 , 2010.
[4] GLA. London data store. http:/, 2011.
[5] D. Ho and K. Imai, Estimating causal effects of ballot order from a randomized natural experiment. Public Opinion Quarterly, 72 (2): 216–240, 2008.
[6] IBM. Many bills: A visual bill explorer. http:/manybills., 2011.
[7] P. Kinnaird, H. Rouzati, and X. Sun, Connect 2 congress. In IEEE Information Visualization Poster Extended Abstracts, Atlantic City, 2009. IEEE.
[8] J. G. Koppell and J. A. Steen, The effects of ballot position on election outcomes. The Journal of Politics, 66 (1): 267–81, 2004.
[9] J. Krosnick, Response strategies for coping with the cognitive demands of attitude measures in surveys. Applied Cognitive Psychology, 5: 213–236, 1991.
[10] F. Lakha, D. Gorman, and P. Mateos, Name analysis to classify populations by ethnicity in public health: Validation of onoMAP in Scotland. Public Health, in press, 2011.
[11] A. Lijphart and R. L. Pintor, Alphabetic bias in partisan elections: Patterns of voting for the spanish senate, 1982 and 1986. Electoral Studies, 7 (3): 225–231, 1988.
[12] P. Mateos, R. Webber, and P. Longley, The cultural, ethnic and linguistic classification of populations and neighbourhoods using personal names. In CASA Working Paper, volume 116. University College London, 2007.
[13] J. Miller and J. Krosnick, The impact of candidate name order on election outcomes. Public Opinion Quarterly, 62 (3): 291–330, 1998.
[14] T. Munzner, Outward and inward grand challenges. In VisWeek08 Panel: Grand Challenges for Information Visualization, Columbus OH, 2008. IEEE.
[15] mySociety. They work for you. http:/, 2011.
[16] OnoMAP. OnoMAP. http:/, 2011.
[17] Ordnance Survey. Ordnance survey opendata. products.html, 2010.
[18] M. Pack, Does the alphabet matter when it comes to Liberal Democrat internal elections? http://bit.lylibdemvoice, 2010.
[19] C. Rallings, M. Thrasher, and G. Borisyuk, Ballot structure, parties and voters: Measuring effects at the local elections 2002-2006. Proceedings, Elections, Opinion Polls and Parties Annual Conference, Nottinghamxz University, 2006.
[20] C. Rallings, M. Thrasher, and C. Gunter, Patterns of voting choice in multimember districts: the case of english local elections. Electoral Studies, 17 (1): 111–128, 1998.
[21] I. Shepherd, Putting time on the map: Dynamic displays in data visualization and GIS. In P. Fisher , editor, Innovations in GIS, volume 2, pages 169–187. Taylor & Francis, London, 1995.
[22] A. Slingsby, J. Dykes, and J. Wood, Configuring hierarchical layouts to address research questions. IEEE Transactions on Visualization and Computer Graphics, 15 (6): 977–984, 2009.
[23] A. Slingsby, J. Dykes, and J. Wood, Tweeting visualizations for collaborative visual analysis. In Poster Proceedings, IEEE Infovis, Salt Lake City, 2010.
[24] The Electoral Commission. Ballot Paper Design. Electoral Commission, London, 2003.
[25] M. Visvalingam, The signed chi-score measure for the classification and mapping of polychotomous data. Cartographic Journal, 18 (1): 32–43, 1981.
[26] H. Wickham, D. Cook, H. Hofmann, and A. Buja, Graphical inference for infovis. IEEE Transactions on Visualization and Computer Graphics, 16 (6): 973–979, 2010.
[27] J. Wood and J. Dykes, Spatially ordered treemaps. IEEE Transactions on Visualization and Computer Graphics, 14 (6): 1348–1355, 2008.
27 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool