tizens to make a decision, and they do it on the basis of reliable information. So much so, that research indicates that voters are now growing used to following the apps’ voting recommendations, provided that they are in line with their political ideas.
Another interesting aspect of the VAAs’ emergence is the extent to which these tools help us to better understand the citizens’ electoral behaviour. We know that people who use them tend to participate more than the average, but it has also been observed that the apps have a different impact on citizens depending on their level of education - and that those who benefit the most from them are the citizens with low levels of education who, after using them, show a greater interest in the electoral processes and a greater disposition to engage in them. If this evidence is confirmed by further studies, it will be a relevant finding indeed, for political participation is closely related to educational and socioeconomic levels.
Besides, citizen behaviour at the polls tend to be consistent with the results they have found in the apps. It is worth noting that only 8 % decide to change their vote when the results they get from the apps do not match what they had expected. In other words, VAAs are very effective in reinforcing citizens’ votes, but not so much in getting them to change their vote, even when the apps place them closer to other political options.
The growth and effectiveness of these tools has led some researchers to want to know better the algorithms that decide the results they give, and even to try to validate them externally. This is not a minor issue. A research carried out in 2010 in Lithuania proved that parties in this country were able to manipulate the results of these apps to their advantage.
In any case, vote guidance apps have clearly opened up the horizons of politological research. In fact, the availability of huge amounts of data is so attractive that some observers, back in 2012, were already warning about the need to study the phenomenon more thoroughly. As a result, analyses of specific cases are increasingly common – Switzerland, Turkey, Belgium, Hungary or the 2014 European elections -, asa are research projects that go into a detailed analysis of user behaviour as he or she browses, or of privacy control during the process.
As we have seen, it seems that vote guidance apps are opening up a new information channel which improves political participation in many respects. The system, however, is not free from criticism. Some authors point out that to call them "vote guiders" implies that the decision to vote can only be taken on the basis of the parties’ political positions. This would of course be a reductionist view since, by considering all parties to be on an equal footing, they do not take into account the real options that each party actually has to come to power and turn its proposals into laws of the land. All parties are labeled in the same way, regardless of their size, leadership, territorial location, government experience, or the possibility of coalitions.
We can address this problem in two ways. A first option would be to incorporate all these factors into the algorithms, so that the system would not only assess the coincidence between political positions, but offer also specific information about each party. This would not be a perfect solution, for it would be obviously biased, but the results would certainly be more realistic. The second option would be to change the narrative about these applications, explaining their purpose – information - and their limitations very clearly, so that people would not expect from them anything but context and complementary information.
In any case, this problem has surfaced due to the widespread use of these apps and their increasing importance in the electoral processes. The VAAs have moved from anecdote to consolidation in the last 10 years and have become a source of information for an increasing number of voters, a driver for electoral participation, and a supplier of quality data on the elect