Kemal Gunay

Computational Social Scientist

Biography

I’m Kemal Günay, a researcher working at the intersection of sociology and data science. Between 2023 and 2024, I served as a Research Data Scientist at the Department of Sociology and Social Research at the University of Trento. My academic work focuses on topics such as user experience, public opinion mining, discourse analysis, social psychology, and new media. I spend much of my time analyzing large-scale social media data to better understand how information and behaviors spread within society.

My expertise lies in social media analytics, combining natural language processing (NLP), social network analysis, and big data techniques. I have conducted projects using data from platforms like Facebook, Instagram, YouTube, and Twitter—working on semantic networks, relational structure analysis, and the fine-tuning of large language models (LLMs) for domain-specific classification tasks. I am especially interested in the discursive and relational dynamics between political figures and their audiences.

I have advanced proficiency in open-source programming languages such as Python and R, along with extensive experience in academic tools such as NVivo, Gephi, and SPSS.

I serve as a reviewer for high-impact SSCI Q1 journals such as New Media & Society, the Journal of Asian Public Policy, and Climate Policy, and I continue to contribute to the fields of computational social science, artificial intelligence, big data, and digital media. I donate at least 10% of my income to effective charities, as I believe that science should not only generate knowledge but also serve the public good.

I’m open to academic collaborations, research projects, and new positions. You can find more detailed information in my CVs in both English and Turkish.

Download my academic CV and resumé .

Interests

Computational Social Science
Machine Learning
Quantitative Text Analysis / NLP
Statistics
Media Studies

Education

PhD in Communication Sciences, 2022

Istanbul University
Communication and Social Sciences (Erasmus)

Universidad San Jorge (Spain)
Corporate Communication

Istanbul University
Music Technology

Bournemouth and Poole College (United Kingdom)
Public Relations and Publicity

Istanbul University

Skills

R

I have 4 years of experience using R for academic works

Statistics

Python

I have 4 years of experience using Python for data science projects

JavaScript

I have begun learning JavaScript this year, specifically using it to scrape data from social media

Docker

AWS

Experience

Lecturer

Bahcesehir University

Sep 2024 – Present Turkey

Responsibilities include:

Field of Study: Media Technologies
I am a coding instructor specializing in Python. I guide students in developing fundamental programming skills and practical applications.
Academic research tools: Python data manipulation, data visualization.

Lecturer

Istanbul Kultur University

Sep 2024 – Present Turkey

Responsibilities include:

Field of Study: Programming for Game Design
I am a coding instructor specializing in Python. I guide students in developing fundamental programming skills.
Academic research tools: Python data manipulation, PyGame.

Postdoc Data Science Researcher

University of Trento

Mar 2023 – Jul 2024 Italy

Responsibilities include:

Field of Study: Research Methods in Digital Media, Data Science, Social Media Analytics
Analysis Methods:: Collecting and managing large databases from major social media platforms; using quantitative analysis methods and techniques; specifically (but not exclusively) analyzing data using techniques from computational linguistics (NLP), network science (social and/or semantic), and machine learning.
Academic research tools: Python & R, data manipulation, data visualization, statistical tests.

Lecturer

Istanbul Aydin University

Jan 2023 – Jun 2023 Istanbul

Responsibilities include:

Field of Study: Research Methods in New Media, Data Science, Social Media Advertising
Analysis Methods:: I teach core courses in the social sciences: research methods and statistics
Academic research tools: Python, RStudio, SPSS, NVivo Software

Ph.D New Media Researcher (Scholar)

Istanbul University

Sep 2019 – Oct 2022 Istanbul

Responsibilities include:

Field of Study: Digital Media, Environmental Communication and Communication Sciences, Data Science, Political Discourse
Analysis Methods: Text mining & NLP; Topic Modelling (LDA, STM), Social Network Analysis, Text Clustering
Academic research tools: Python, RStudio, SPSS, NVivo Software

Data Scientist

Data Science & ML School

May 2021 – Jan 2022 Istanbul

Responsibilities include:

Performing data extraction, manipulation, feature engineering and visualization. Applying statistical testing and ML techniques: hypothesis testing, classification, regression.
Working with ML algorithms and models (SVM, NB, RF, LR, PCA, Rule- Based) and their underlying computational and probabilistic statistics.
Hands-on-experience via projects; CRM Analytics; AB Test, Recommendation Systems; Measurement, Regression, Classification and Time Series Problems, Demand Forecasting and et al.

Researcher

Istanbul Gelisim University

Jan 2018 – Aug 2019 Istanbul

Responsibilities include:

Field of Study: Digital Media and Communication Sciences, NLP & Text Mining, Data Visualization, Machine Learning
Academic research through Python, RStudio, SPSS, NVivo Software

Projects

Association Rule Learning ARL - Apriori Shopping

Association rule learning is a rule-based machine learning approach for finding significant connections between variables in large databases. It is designed to identify strong rules that have been identified in databases using various measures of interests tool that can help businesses and other organizations manage their interactions with customers.

Building social networks from text

Constructing social networks from unstructured text is an issue of great interest that receives little research. In my most recent blog article, I describe how I built a social network.

CLTV - Customer Lifetime Value Method

Lifetime value is a critical metric because it represents the maximum amount that customers may be expected to spend in order to acquire new ones. As a result, it’s crucial in determining the payback of marketing expenses used in marketing mix modeling.

Comprehensive Guide to Build Recommendation Engine

In this notebook, We will discuss three types of recommender system; (1)Association rule learning (ARL), (2)content-based and (3)collaborative filtering approaches. In this notebook, we will explain how to build a recommender system with these three methods.

Constructing knowledge graphs from text using OpenAI functions

Building knowledge graphs from unstructured text is an issue of great interest that receives little research. In my most recent blog article, I describe how I built a knowledge network in Neo4j using the LangChain framework and OpenAI functions. Along with learning all the subtleties of employing LLMs to build a knowledge graph, you will also learn the necessary procedures to develop a production information extraction pipeline.

Customer Relationship Management | CRM Analytics

Customer Relationship Management (CRM) system is an information management and analysis tool that can help businesses and other organizations manage their interactions with customers.

Deep Neural Networks with Tensorflow & Keras

Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised

Geolocation Algorithm From Text to Location

In this task, you are required to create an algorithm that takes as input a pdf file corresponding to a research publication and outputs a list of all geographical locations mentioned in the publication. For each geographical location, the algorithm will have to additionally identify the country that the location belongs to, and return a latitude- longitude pair corresponding to the centroid of the respective country.

Getting Started with Image Preprocessing in R

A few problems associated with image data include complexity, inaccuracy, and inadequacy. This is why before building a computer vision model, it is essential that the data is preprocessed (cleaned and processed to the desired format) to achieve the desired results.

ggplot example

How to use ggplot library

LDA Topic Modeling - Bill Gates Tweets

Republic Day (29 October 1923) Republic Day (Turkish Cumhuriyet Bayramı) is a public holiday in Turkey commemorating the proclamation of the Republic of Turkey, on 29 October 1923. The annual celebrations start at 1:00 pm on 28 October and continue for 35 hours.

Multi Class Text Classification with LSTM

Family of linear algebra algorithms for identifying the latent structure in data representAs we have previously shown, machine learning may be used in a variety of ways to automatically classify texts or documents.

PySpark ML Churn Analysis

Customer Relationship Management (CRM) system is an information management and analysis tool that can help businesses and other organizations manage their interactions with customers.

Quora Topic Modeling_scikit learn_NMF

Family of linear algebra algorithms for identifying the latent structure in data represented as a non-negative matrix. NMF can be applied for topic modeling, where the input is term-document matrix, typically TF-IDF normalized. Input; Term-Document matrix, number of topics. Output; Two non-negative matrices of the original n words by k topics and those same k topics by the m original documents.Basically, we are going to use linear algebra for topic modeling.

RFM Analysis | Recency, Frequency, Monetary

How often do you use the RFM analysis in your marketing? The RFM analysis is a great tool for marketers to figure out which customers are most valuable and how they should be marketed to. It’s also a great way to find new prospects that might not have been found otherwise. Here we’ll explain into each of the four groups. Retention, Frequency, Monetary Value and Referral and explain what they mean and why you want them as customers!

Salary Prediction ML Pipeline Main Function

Companies want their data science teams to speed up the process so they can deliver valuable business predictions faster. That’s where ML pipelines come in. By automating workflows with machine learning pipeline monitoring, ML pipelines bring you to operationalizing machine learning models sooner.

Social Network Analysis - Community Detection R

Social network analysis (SNA) is the process of investigating social structures through the use of networks and graph theory. It characterizes networked structures in terms of nodes (individual actors, people, or things within the network) and the ties, edges, or links (relationships or interactions) that connect them.

Spotify User Profile Analysis With Spotifyr — RStudio

Spotifyr is an R wrapper for pulling track audio features and other information from Spotify’s Web API in bulk. You can easily analyze your listining records.

Topic Modeling - Sentiment Analysis | Mustafa Kemal Ataturk Nutuk | Book Analysis

Republic Day (29 October 1923) Republic Day (Turkish Cumhuriyet Bayramı) is a public holiday in Turkey commemorating the proclamation of the Republic of Turkey, on 29 October 1923. The annual celebrations start at 1:00 pm on 28 October and continue for 35 hours.

Recent Publications

Quickly discover relevant content by filtering publications.

Kemal Gunay, Yesim Gucdemir (2022). Topıc Modelıng Analysıs Of NGO’s Twıtter Postıngs Between 2020-2021 In Turkey Wıthın The Context Of Clımate Change Communıcatıon. The Turkish Online Journal of Design Art and Communication, 12(4).

Cite Slides

Kemal Gunay, Yesim Gucdemir (2021). Digital Seige - Is the Internet of Things Transforming a Surveillance Tool?. Istanbul University Press, 5281(5281).

Cite Slides

Kemal Gunay, Seda Mengu, Murat Mengu (2021). Value-based Communication During COVID-19 Pandemic - A Study on The Twitter Messages of Turkish Ministry of Health. Athens Journal of Mass Media and Communications, 7(1).

Cite

Kemal Gunay, Yesim Gucdemir, Seda Mengu (2020). An Investigation of Candidate Leaders’ Tweet Campaigns Prior to the Istanbul Metropolitan Municipal Elections Using Big Data Text Mining. Connectist: Istanbul University Journal of Communication Sciences, 59(59).

Cite Code Slides

Kemal Gunay

Computational Social Scientist

Biography

Skills

Experience

Recent Posts

Projects

Recent Publications