Sentiment Analysis of Turkish Political News

Kaya, Mesut
Fidan, Guven
Toroslu, İsmail Hakkı
In this paper, sentiment classification techniques are incorporated into the domain of political news from columns in different Turkish news sites. We compared four supervised machine learning algorithms of Naive Bayes, Maximum Entropy, SVM and the character based N-Gram Language Model for sentiment classification of Turkish political columns. We also discussed in detail the problem of sentiment classification in the political news domain. We observe from empirical findings that the Maximum Entropy and N-Gram Language Model outperformed the SVM and Naive Bayes. Using different features, all the approaches reached accuracies of 65% to 77%.


Transfer Learning Using Twitter Data for Improving Sentiment Classification of Turkish Political News
Kaya, Mesut; Fidan, Guven; Toroslu, İsmail Hakkı (2013-10-29)
In this paper, we aim to determine the overall sentiment classification of Turkish political columns. That is, our goal is to determine whether the whole document has positive or negative opinion regardless of its subject. In order to enhance the performance of the classification, transfer learning is applied from unlabeled Twitter data to labeled political columns. A variation of self-taught learning has been proposed, and implemented for the classification. Different machine learning techniques, including...
Partisan selective news exposure and political polarization on twitter networks in Turkey
Gölcük, Seyit; Yavuz, Nilay; Department of Political Science and Public Administration (2018)
This thesis aims to investigate the degree of partisan selective exposure, political polarization and their statistical association by using a Twitter data derived from Turkish political Twitter networks. Analysis of a sample of 2.790.339 unique users who have a total of 48.316.548 following links to political news outlets and political entities on Twitter reveals that, Turkish Twitter audiences identified with a political party exercise very high levels of partisan selective exposure to like-minded news ou...
Spatial analysis of contemporary Turkish elections: a comprehensive approach
Özen, İlhan Can (2017-01-01)
This study offers a comprehensive approach to spatial analysis of parliamentary elections in Turkey since 2002. Using advanced spatial models, we find that electoral competitiveness and concentration mostly stabilized in the Western subprovinces whereas they are still in flux in the Eastern and Southern regions. There is an increasing level of geographically dependent concentration and competitiveness in recent elections, particularly in the 2015 elections (June and November). Our analyses also show that wh...
Clustering based personality prediction on Turkish Tweets
Tutaysalgır, Esen; Toroslu, İsmail Hakkı; Department of Computer Engineering (2019)
In this thesis, we present a framework for predicting the personality traits of users using their tweets written in Turkish. The prediction model is constructed with a clustering based approach. We show how to extract linguistic features from tweet data and to adapt TF-IDF weighting and word embeddings to the Turkish tweets. Since the model is based on linguistic features, it is language specific. The prediction model uses features applicable to Turkish language and related to writing style of Turkish Twitt...
Politics and the Mass Media in Turkey
Kaya, Ahmet Raşit; Çakmur, Barış (Informa UK Limited, 2010-01-01)
This article sets out to examine the linkages between the media and politics in Turkey. It argues that, rooted in the world of politics from the outset, Turkish media has always been marked by a high degree of political parallelism. As regulator and funder, the state, making up the political majority, exerted strong control over the media. In the 1990s, the shift to a globalized market and the explosive growth of private broadcasting did not decrease the high degree of political parallelism. Instead, it ena...
Citation Formats
M. Kaya, G. Fidan, and İ. H. Toroslu, “Sentiment Analysis of Turkish Political News,” 2012, Accessed: 00, 2020. [Online]. Available: