webomurga/CMPE59U_Social_Media

Mapping Climate Policy Discourse in Turkey - A Topic Modeling Analysis of Parliamentary and Social Media Debates (2021-2025)

Dataset Summary

This dataset contains Turkish-language social media posts related to public discourse on environmental legislation in Türkiye, specifically focusing on the Climate Law (İklim Kanunu) and the Water Law (Su Kanunu).

The dataset covers the period 2021–2025 and includes content collected from Facebook, Twitter (X), Ekşi Sözlük, and DonanımHaber Forum. It is designed to support research on public opinion, sentiment analysis, argumentation patterns, and policy-related discourse in social media.

Contextual Usage

• Climate Law Posts: Primarily used for retrospective analysis, as the law has arguably been enacted or is in advanced stages.
• Water Law Posts: Intended for forecasting public reactions to upcoming bill proposals.

All data was collected from publicly available content and processed for non-commercial research purposes only.

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Supported Tasks

• Sentiment Analysis: (Labels provided via savasy/bert-base-turkish-sentiment-cased)
• Argument Classification: (Sub-topics identified via LDA)
• Policy Discourse Analysis
• Social Media Text Analysis (Turkish)

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Dataset Structure

Each row in the dataset represents a single social media post or comment.

Data Fields

Column Name	Description
Name	Anonymized user name
Profile ID	User identifier
Date	Timestamp of the post
Likes	Number of likes or reactions (if available)
Comment	The actual text content of the post
Platform	Source platform (Facebook, Twitter, Ekşi Sözlük, DonanımHaber Forum)
Post ID	Unique identifier of the original post
Topic	Keyword used for scraping (e.g., iklim_kanunu, su_kanunu)
Original Post?	Boolean indicating if the entry is an original post or a reply/comment
Sentiment	Sentiment label (positive/negative) predicted using savasy/bert-base-turkish-sentiment-cased
Argument	Sub-topic label identified using LDA topic modeling (See table below)

Argument Labels (LDA Topics)

The Argument column represents sub-topics of discussion derived from Latent Dirichlet Allocation (LDA) topic modeling.

Argument Label	Description	Top Words (Examples)
Energy Policy	Fossil fuels, carbon, and energy policies	iklim, fosil, yakıt, karbon, enerji
Climate Crisis	Crisis related to fossil fuels & politics	klim, fosil, yakıt, türkiye, krizinin
Green Activism	Protests and global activism	fosil, yeşile, küresel, protesto
Intl Conferences	COP and international summits	iklim, konferansı, taraflar, birleşmiş milletler
Ministry Actions	Actions by the Ministry of Environment	çevre, şehircilik, bakanlığı, murat (kurum)
Urban Policy	Urban transformation and TOKİ	devlet, kentsel, toki, dönüşüm
Bill Proposal	Parliamentary bill proposals	tbmm, genel, kurulu, teklifi
Green Legislation	Green Deal and adoption processes	yeşil, mutabakat, kanun, kabul
Approval Process	Legislative approval/acceptance	kabul, tbmm, meclis, edildi
Emissions Trading	ETS, carbon tax, greenhouse gas	emisyon, sera, ticaret, karbon
Politics & Forests	Political decisions on forestry	orman, geri, çekildi, erdoğan
Enactment	Official Gazette publication	resmi, gazete, yürürlüğe, girdi
Policy Debates	General debates on climate policy	iklim, karbon, hayir, küresel
Water Mgmt	Water management and irrigation	sulama, gölü, suyu, yönetimi, taşkın
Agri Risks	Agricultural risks (drought/rain)	yağmur, tarımsal, tehdit, hasat
Weather Alerts	Meteorological warnings	meteoroloji, alarmı, şiddetli, acil
Drought Crisis	Regional drought impacts	kuraklık, su, tehlikesi, krizi
Food Security	Food supply and natural disasters	gıda, doğal, afet, korumak
Desertification	Desertification and soil loss	çölleşme, mücadele, toprak, erozyon
Forest Threats	Global warming threats to forests	ormanlık, yangın, tehdit
Env Awareness	General environmental awareness	ısınma, çevre, koruma, bilinç
Temp Rise	Rising temperatures/Heatwaves	sıcak, ısınma, derece, artış
Climate-Drought	Climate change causing drought	iklim, değişikliği, kuraklık
Fire Containment	Status of forest fire control	kontrol, altına, alındı, söndürme
Firefighting	Active firefighting operations	yangın, müdahale, havadan, uçak
Evacuations	Evacuations due to disasters	tahliye, zarar, can, kaybı

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Data Collection and Processing

• Time Span: 2021–2025
• Sources: Publicly accessible posts from Facebook, Twitter (X), Ekşi Sözlük, and DonanımHaber Forum.
• Methodology:
  • Data was scraped using topic-specific keywords (iklim_kanunu, su_kanunu).
  • Sentiment Analysis was performed automatically using the Hugging Face model savasy/bert-base-turkish-sentiment-cased.
  • Argument Sub-topics were extracted using unsupervised LDA topic modeling.
  • Anonymization: Usernames and profile identifiers have been anonymized to protect user privacy.

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Ethical Considerations

This dataset contains user-generated content from social media platforms. Although the data was publicly available at the time of collection:

• Privacy: Personal identifiers have been anonymized.
• Usage: The dataset should not be used to identify, profile, or target individuals.
• Scope: No private messages or restricted content were included.
• Bias: The dataset may reflect platform-specific biases and does not necessarily represent the full population of Türkiye.
• Language: Social media text may contain informal expressions, sarcasm, or offensive language.

Researchers are encouraged to follow platform-specific terms of service and ethical research guidelines when using this dataset.

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Citation

If you use this dataset in your research, please cite it as follows:

@misc{turkish-env-social-media-2026,
  title = {Mapping Climate Policy Discourse in Turkey - A Topic Modeling Analysis of Parliamentary and Social Media Debates (2021-2025)},
  author = {Yıldırım, Cansu Mine and Buldu, Murat and Akdağ, Hüseyin Emir and Kahraman, Sena},
  year = {2026},
  publisher = {HuggingFace},
  howpublished = {\url{[https://huggingface.co/datasets/webomurga/CMPE59U_Social_Media](https://huggingface.co/datasets/webomurga/CMPE59U_Social_Media)}}
}