Cetin, UzayGundogmus, Yunus Emre2024-07-182024-07-182018978-1-5386-7893-0https://hdl.handle.net/11411/85153rd International Conference on Computer Science and Engineering (UBMK) -- SEP 20-23, 2018 -- Sarajevo, BOSNIA & HERCEGIn this study, we conduct a data-driven study to harvest the decision makers' policy orientation and predict their votes. We collect and analyze the data about the opinion of the individual voters on a variety of political issues related to Turkish politics. Based on this data, we can measure which parties are close and which parties are distant in multi-dimensional political space. We can make a glimpse to what social matters shape the Turkish political climate with the lenses of statistical models. We show in which political issues Turkish people agree on the most and in which political issues they are segregated the most. Moreover, by using traditional machine learning tools, we try to predict the vote of an individual, depending on his or her opinion about the pre-determined political issues with the help of our data.eninfo:eu-repo/semantics/closedAccessPolitical Data ScienceApplied Machine LearningComputational Social ScienceConference Object2-s2.0-85060660341541N/A537N/AWOS:000459847400104