arXiv subjects

Oğuz Gürerk

Publications and source records attributed to Oğuz Gürerk.

3 recordsLinked to original sources

arXiv2023

Validating Digital Traces with Survey Data: The Use Case of Religiosity

This paper tests the validity of a digital trace database (Politus) obtained from Twitter, with a recently conducted representative social survey, focusing on the use case of religiosity in Turkey. Religiosity scores in the research are extracted using supervised machine learning under the Politus project. The validation analysis depends on two steps. First, we compare the performances of two alternative tweet-to-user transformation strategies, and second, test for the impact of resampling via the MRP technique. Estimates of the Politus are examined at both aggregate and region-level. The results are intriguing for future research on measuring public opinion via social media data.

cs.SI↗

arXiv2022

On a Notion of Outliers Based on Ratios of Order Statistics

There are a number of mathematical formalisms of the term "outlier" in statistics, though there is no consensus on what the right notion ought to be. Accordingly, we try to give a consistent and robust definition for a specific type of outliers defined via order statistics. Our approach is based on ratios of partial sums of order statistics to investigate the tail behaviors of hypothetical and empirical distributions. We simulate our statistic on a set of distributions to mark potential outliers and use an algorithm to automatically select a cut-off point without the need of any further a priori assumption. Finally, we show the efficacy of our statistic by a simulation study on distinguishing two Pareto tails outside of the Lévy stable region.

stat.ME↗

arXiv2021

A study on random permutation graphs

For a given permutation $π_n$ in $S_n$, a random permutation graph is formed by including an edge between two vertices $i$ and $j$ if and only if $(i - j) (π_n(i) - π_n (j)) < 0$. In this paper, we study various statistics of random permutation graphs. In particular, the degree of a given node, the number of nodes with a given degree, the number of isolated vertices, and the number of cliques are analyzed. Further, explicit formulas for the probabilities of having a given number of connected components and isolated vertices are obtained.

math.CO↗