Kemal Günay

Kemal Günay

Ph.D. Computational Social Scientist

Istanbul University

Biography

Ben Kemal Günay. Sosyoloji, iletişim ve veri bilimi kesişiminde çalışan bir araştırmacıyım. 2023-2024 yılları arasında Trento Üniversitesi Sosyoloji ve Sosyal Araştırmalar Bölümü’nde Araştırmacı Veri Bilimci olarak görev yaptım. Akademik çalışmalarımda, kullanıcı deneyimi, kamuoyu madenciliği, söylem analizi, sosyal psikoloji ve yeni medya gibi konulara odaklanıyor; toplumsal bilginin ve davranışların dijital ortamlarda nasıl yayıldığını anlamaya çalışıyorum.

Uzmanlık alanım sosyal medya verileri üzerinde doğal dil işleme (NLP), sosyal ağ analizi ve büyük veri analitiğini bir araya getiren çok disiplinli çalışmaları kapsıyor. Facebook, Instagram, YouTube ve Twitter gibi platformlardan elde ettiğim verilerle semantik ağlar, ilişkisel yapı analizleri ve büyük dil modellerinin (LLM) yeniden eğitilmesi üzerine projeler yürütüyorum. Özellikle politik aktörler ile kitleleri arasındaki söylemsel ve ilişkisel dinamiklere odaklanıyorum.

Python ve R gibi açık kaynak yazılım dillerine ileri düzeyde hâkimim; aynı zamanda NVivo, Gephi ve SPSS gibi sosyal bilimlerde yaygın olarak kullanılan yazılımlarla da kapsamlı deneyime sahibim.

New Media & Society, Journal of Asian Public Policy ve Climate Policy gibi yüksek etkili SSCI Q1 dergilerde hakemlik yapıyorum ve hesaplamalı sosyal bilimler, yapay zeka, büyük veri ve dijital medya alanlarına katkıda bulunmaya devam ediyorum. Gelirimin en az %10’unu etkili yardım kuruluşlarına bağışlıyorum; çünkü bilimin yalnızca bilgi üretmekle kalmayıp, topluma da hizmet etmesi gerektiğine inanıyorum.

Akademik iş birliklerine, projelere ve yeni pozisyonlara açığım. Daha ayrıntılı bilgi için Türkçe ve İngilizce özgeçmişlerime göz atabilirsiniz.

Download my academic CV and resumé .

İlgi alanları
  • Hesaplamalı Sosyal Bilimler
  • İklim Değişikliği İletişimi
  • Doğal Dil işleme / NLP
  • İstatistik
  • Medya ve Kültürel Çalışmalar
Eğitim

  • PhD Halkla İlişkiler ve Tanıtım, 2022

    Istanbul Universitesi

  • 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

Akademik çalışmalar için R kullanma konusunda 5 yıllık tecrübem bulunmaktadır.

Statistics

Betimsel istatistik, parametrik testler, non-paraöetrik testler

Python

Veri bilimi ve akademik çalışmalar için yaklaşık 4 yıldır Python kullanmaktayım

JavaScript

Sosyal medyadan veri kazıma ve otomizasyon için kullanıyorum

Docker
AWS

Experience

 
 
 
 
 
Postdoc Data Scientist
University of Trento
Mar 2023 – Present Istanbul

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.
 
 
 
 
 
Ph.D Lecturer
Istanbul Aydin University
Oca 2023 – Haz 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
 
 
 
 
 
Istanbul University
Ph.D New Media Researcher (Scholar)
Istanbul University
Eyl 2019 – Eki 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 Science & ML School
Data Scientist
Data Science & ML School
Mayıs 2021 – Oca 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.
 
 
 
 
 
Istanbul Gelisim University
Researcher
Istanbul Gelisim University
Oca 2018 – Ağu 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

Recent Posts

LLM - Encoder - Embedding - Decoder
Büyük dil modelleri (LLM - Large Language Models) bağlamında encoder, embedding ve decoder kavramları çok önemli roller oynar. Bu kavramları, Transformer tabanlı modellerle ilişkilendirerek açıklayalım.
Kemal Günay, Kemal Günay
Mar 11, 2025 2 min read LLM, Doğal Dil İşleme - NLP
LLM - Encoder - Embedding - Decoder
TEST BLOG Welcome to Wowchemy, the website builder for Hugo
TEST Welcome 👋 KEMAL We know that first impressions are important, so we’ve populated your new site with some initial content to help you get familiar with everything in no time.
Kemal Günay, 吳恩達
Ara 13, 2020 2 min read Demo, 教程
TEST BLOG Welcome to Wowchemy, the website builder for Hugo
TEST Synthetic Data
Welcome 👋 KEMAL We know that first impressions are important, so we’ve populated your new site with some initial content to help you get familiar with everything in no time.
Kemal Günay
Ara 13, 2020 2 min read Demo, 教程
TEST Synthetic Data
Display Jupyter Notebooks with Academic
Learn how to blog in Academic using Jupyter notebooks
Kemal Günay
Last updated on Eyl 5, 2019 2 min read
Display Jupyter Notebooks with Academic

Projects

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All NLP Network Science Business Intelligence Other
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.
Association Rule Learning ARL - Apriori Shopping
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.
Building social networks from text
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.
CLTV - Customer Lifetime Value Method
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.
Comprehensive Guide to Build Recommendation Engine
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.
Constructing knowledge graphs from text using OpenAI functions
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.
Customer Relationship Management | CRM Analytics
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
Deep Neural Networks with Tensorflow & Keras
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.
Geolocation Algorithm From Text to Location
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.
Getting Started with Image Preprocessing in R
ggplot example
How to use ggplot library
Slaytlar Follow
ggplot example
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.
LDA Topic Modeling - Bill Gates Tweets
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.
Multi Class Text Classification with LSTM
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.
PySpark ML Churn Analysis
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.
Quora Topic Modeling_scikit learn_NMF
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!
RFM Analysis | Recency, Frequency, Monetary
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.
Salary Prediction ML Pipeline Main Function
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.
Social Network Analysis - Community Detection R
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.
Spotify User Profile Analysis With Spotifyr — RStudio
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.
Topic Modeling - Sentiment Analysis | Mustafa Kemal Ataturk Nutuk | Book Analysis

Recent Publications

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Kemal Günay, 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 Slaytlar

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

Cite Slaytlar

Kemal Günay, 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 Günay, 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).

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