Dmitry Erokhin, research scholar at the International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria, synthesis research on how digital data can help identify and respond to misinformation and fast-changing public narratives. Dmitry Erokhin’s studies analyze digital trace data such as search trends and large-scale online discussion to understand what people pay attention to, how uncertainty spreads, and where communication gaps emerge during high-impact events.

Dmitry Erokhin’s research focuses on a practical question: when events unfold faster than traditional reporting cycles, how can public institutions and researchers use publicly available online signals to improve situational awareness without relying on speculation? Across multiple applications, Dmitry Erokhin shows how online behavior can be measured using reproducible methods such as time-series analysis of search interest, and natural language processing (NLP) for topic and sentiment patterns in public comments to complement conventional data sources.

Real-world implications of Dmitry Erokhin’s research are strongest in crisis communication and disaster risk reduction. Digital trace data can be used to:

detect early spikes in attention and information demand (for example, rapid increases in searches after an incident);
map the dominant questions and concerns that people express publicly;
identify the emergence of rumor themes that can undermine protective behavior; and
measure whether corrective information is reaching and engaging audiences over time.
In practice, this type of monitoring can help communicators prioritize what to clarify first, tailor messages to the language and concerns actually appearing online, and evaluate whether misinformation narratives are gaining traction or fading.

Dmitry Erokhin’s publications also show that misinformation management is not limited to fact-checking single claims. Instead, Dmitry Erokhin treats misinformation as a dynamic process shaped by attention, emotion, and amplification. For example, Dmitry Erokhin’s studies examine how conspiracy discussions fluctuate around disasters and how platform-scale discourse can be assessed for sentiment and topic shifts during disruptive events. These approaches can help practitioners anticipate secondary impacts, such as decreased trust or reduced compliance with safety guidance.

Beyond emergencies, Dmitry Erokhin applies the same digital-data toolkit to governance-relevant topics where public trust and information quality matter, including analyses of how audiences engage with ESG reporting content on YouTube and how search behavior can be used to study cross-national political attention around elections. These studies illustrate how digital data can support evidence-based communication strategies in areas where misunderstanding, polarization, or low trust can distort decision-making.

Dmitry Erokhin also emphasizes responsible use. Digital trace data can be incomplete, platform-biased, and sensitive to changes in algorithms and access rules. For that reason, Dmitry Erokhin’s work repeatedly highlights the need for careful interpretation, transparent methods, and privacy-aware practices using aggregated signals, minimizing identifiable information, and treating online content as one input among several rather than a standalone truth source.”

“Digital data can provide early signals about what people are concerned about and where communication gaps may be forming”, said Dmitry Erokhin. “The goal is to translate large volumes of open online information into structured evidence that can support timely and transparent decisions”.

Selected publications by Dmitry Erokhin (with DOIs):

ESG Reporting in the Digital Era: Unveiling Public Sentiment and Engagement on YouTube. DOI: 10.3390/su17157039
Applying Google Trends to Analyze Electoral Outcomes: A 2024 Cross-National Perspective. DOI: 10.1016/j.ssaho.2025.101846
Analyzing Spanish-Language YouTube Discourse During the 2025 Iberian Peninsula Blackout. DOI: 10.3390/soc15070174
Public Discourse Surrounding the 2025 California Wildfires: A Sentiment and Topic Analysis of High-Engagement YouTube Comments. DOI: 10.3390/geosciences15030100
Social Media Data for Disaster Risk Management and Research (with co-authors). DOI: 10.1016/j.ijdrr.2024.104980
Earthquake Conspiracy Discussion on Twitter (with co-authors). DOI: 10.1057/s41599-024-02957-y
COVID-19 Conspiracy Theories Discussion on Twitter (with co-authors). DOI: 10.1177/20563051221126051
Unveiling the Dynamics of Climate Change Narratives: A Google Trends Analysis (with co-authors). DOI: 10.15847/obsOBS18520242567