Professor Susan Banducci, Director of Exeter Q-Step Centre and member of the Centre for Elections, Media & Participation (CEMaP) at the University of Exeter and Carl Miller, Research Director of the Centre for the Analysis of Social Media (CASM) at Demos. give evidence to the House of Lords Select Committee on Political Polling and Digital Media on the digital impact of polling.

Congratulations to Claudia Zucca, Marie Curie Early Stage Researcher working on the VOTEADVICE project, for her nomination as UK Data Service Data Impact Fellow.
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Read more about her research here

Theresa May's commitment to Brexit may stand somewhat at odds with the source of her popular support, according to our first look at the Kieskompas--VOTEADVICE post-referendum study wave, dated 28 June–10 July. 

The plot below shows her support is highest among those reporting regret about their Leave vote. Our figures are based on a subset of 519 respondents who reported having voted Conservative at the 2015 General Elections, out of a stratified-weighted sample of 2,251 respondents. Our model is predictive of May's support on a 10-point scale, as a function of respondents' referendum vote (discarding participants who did not vote), as well as whether they regret their vote choice.

Sample strata reflect the UK's 12 regions ('NUTS1' including Scotland, Wales, and Northern Ireland), as well as the demographic categories of age (above 18) and gender. We calculated post-stratification weights to adjust the observed proportions to relevant statistics reported by the Office of National Statistics 2015 mid-year estimates. Online, opt-in samples such ours (participants signed up through our 'Election Compass' tools here and here) attract disproportionately many young and politically interested users. Thus we made further adjustments to account for other sources of selection bias: via Iterative Proportional Fitting, we adjusted for the distribution of political interest UK-wide as estimated by the British Election Study, for labour force status as reported by the ONS 2016 Labour Market Study, and for vote in the 2016 Brexit referendum, including turnout.

Theresa May's approval is estimated to be between 4.5–4.76 among the general voting age population, measured on a 10-point scale.  The plot above is based on a linear model focusing on the subset of Conservative voters as of GE2015, and predicts approval (β0 = 4.09, t(489) = 26.28, p < .001.) as a function of the Brexit vote (β = 4.35, t(489) = 5.45, p < .001.), regret over the vote (β = 2.56, t(489) = 8.99, p < .001), and their interaction (β = -4.52, t(489) = -4.77, p < .001). 

We have also looked at the sources of her support in the general population. We have found no substantive predictors of her approval other than partisanship, Conservatives being the most likely to support her while other party supporters are more prone to dislike her. We have found no support of a gender gap in her approval either.

Watch out for more updates as we are aiming to come back with further and more detailed reports on 'Brexit' political behaviour, as well as more information about our samples and data quality.

Hillary Clinton is the presumptive Democratic Party nominee for 2016 US presidential election. No woman has ever won the nomination of a major political party let alone winning the presidency of the US. 
What would happen if Clinton were elected? There may be shifts in policy or issue emphasis but we would also expect these shifts to occur with a male candidate elected president. However, she could, being the first woman president, improve the math scores of girls. One effect that would be unique to Clinton being the first female president is that she could help to reverse negative stereotypes of women.
In what is known as stereotype threat effect, girls underperform on math tests because they feel anxious that they might confirm the negative stereotype that girls are not good at math. However, strong role models in counter-stereotypic roles help to reduce the effects of negative stereotypes.
There is actually evidence that something similar happened for black students when Barack Obama was elected president of the US in 2008. As the first black president, Obama’s election defied negative racial stereotypes and should therefore reduce anxiety for black Americans when confronted with a situation where they may confirm negative stereotypes. 
In an article appearing in the Journal of Experimental Social Psychology, David Marx and his co-authors showed that indeed the stereotype threat effect was reduced. Based on a study of 84 black students and 388 white students, they show that the performance gap between white and black students on a standardized test disappeared during the time of Obama’s convention speech when nominated as the Democratic Party candidate and when first elected as president in 2008.  The study notes that the performance gap was narrowest when there were positive images of Obama’s achievements in the media.
Might we see a similar effect on negative stereotypes for girls if Clinton were to be elected president? As well as helping to reverse negative stereotypes, Clinton as the first female president may also reduce the stereotype that politics and especially the role of elected political leaders on the global stage is not just a man’s world. Hillary Clinton will act as a role model and demonstrate for girls and women that it is acceptable to be interested in politics, they can make a difference and to be ambitious is acceptable.

Reference:
Marx, David M., Sei Jin Ko, and Ray A. Friedman. "The “Obama effect”: How a salient role model reduces race-based performance differences. “Journal of Experimental Social Psychology 45.4 (2009): 953-956.

​Critics argue that one of the main drawbacks of VAA data is the lack of representativeness. Indeed, VAA sites disproportionately attract young, highly educated males from urban areas who have high levels of interest in politics. Consequently, the data generated through these sites mostly reflects the views and attitudes of specific sectors of the population. This, technically speaking, constitutes a so called self-selection bias. However the self-selection bias can in some settings bring about certain advantages does make the VAA data unique and valuable.
When comparing VAA data with traditional survey data, one would expect the latter to be undeniably superior, but that is too simplistic and not exactly true. For the sake of comparison, we take a sample of UK VAA users that consulted the tool for the 2009 elections for the European Parliament and participated in the follow-up survey, and the UK sample from the 2009 European Election Studies (EES). The VAA sample (N=1104) suffers from a double self-selection bias: besides the “usual” self-selection bias affecting VAAs, only a fraction of the participants filled up the additional follow-up questionnaire  containing some of the relevant political questions. The EES sample (N=1000) has national coverage, targeted the population aged 18 and above, and used RDD for selecting the households and the most recent birthday in the household for the selection of respondents. Up until this point, the EES sample seems the better one, as expected.

​A more careful look at the differences between the two samples challenges that ranking. The EES sample has a response rate of only 18%, but to correct for sampling disparities, the data was weighted on age, sex and region. The chart presented above illustrates the main differences between the VAA and the EES sample (which serves here as an example of traditional survey) in terms of respondents’ overrepresentation.
While the younger age categories are overrepresented in the VAA sample, they are underrepresented in the EES one. While the highly educated make up the most of the VAA sample, the traditional one over represents those with low levels of educational attainment. While males are overrepresented in the VAA sample, in the EES one are the females. Further on, when it comes to party affiliation, one can notice that while mainstream party supporters are overrepresented in the EES sample, the VAA one offers the opposite picture, capturing opinions of the smaller parties’ supporters. Finally, while most of the EES respondents present low and very low levels of political interest, the VAA users are very interested in political matters.
One can argue that the VAA sample lacks important information on specific demographic categories and other variables of interest. But a trained eye can see that the VAA sample brings valuable information on the political preferences of those demographic categories that are usually underrepresented by the traditional surveys, such as age, gender and educational attainment. Furthermore, it offers information on the niche party supporters that are harder to reach through traditional means.
 
Resources:
http://eeshomepage.net/ees-2009-study/voter-study/
http://dvn.eudo.eu/dvn/dv/euprofiler

Digital News has produced a short video compiling digital communication lessons for political campaigns. VoteAdvice findings were used to sum up lesson number 3, referring that social media is not the best way to involve youngsters in politics yet. Digital News' lesson concludes: even if you know where is your target audience, you still need to learn how to communicate with it.
The Spanish audio explains: "The research group VoteAdvice whose aim is to investigate how new technologies and social media influence political and social behaviour has published a report based on the participation of people between 18 and 25 years old during the UK election. The conclusion confirms that even when youngster are the main users of social media, they do not use it to express their political opinions"

The votes have been cast and the results are in.
As we reflect on the results of last week’s General Election, Professor Susan Banducci and her colleagues from VoteAdvice* have been thinking about how engaged the under 25, youth, voters have been with the electoral process.
You can follow VoteAdvice on Twitter.