The European Parliament (EP) is viewed as a normal parliament. Voting patterns of its members (MEPs) are mainly aligned with transnational political groups, not national cleavages. Yet, it has been proven by many that MEP voting patterns are an outcome of conflicting pressures and a distorted indicator of their individual political orientations. In this study we rely on MEP written questions to the European Commission to measure the policy positions and their determinants. Using the universe of 100,000+ such questions in 2002-2015 linked with MEP country and European Political Group affiliation data, we test whether one issue of high sensitivity to their domestic audiences-Russia-makes the MEPs take their nationality seriously and pay more attention to it regardless of their transnational partisan affiliations. We rely on supervised machine learning to uncover sentiment of every question asked on a negative-positive scale. Then we contrast the sentiment of questions related to Russia with the rest of questions conditional on party and national affiliation of the MEP asking the question. We find that (i) MEP question involving Russia is twice as negative in tonality as an average question, (ii) more variation in modality of Russia-related questions is explained by MEP national affiliation than her EPG. Our findings are robust to alternative methods of sentiment extraction and to controlling for time-invariant unobserved heterogeneity of MEPs. JEL Classification: F55.