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Ezgi Arslan, PhD.

Ezgi Arslan, PhD.

Industry Analyst
82 Articles
Stay up-to-date on B2B Tech

Ezgi is an industry analyst at AIMultiple.

Research focus at AIMultiple

  • AI agent applications in finance where she combines her finance expertise with emerging AI tools.
  • Sustainability where she relies on her academic research background.
  • Procurement technologies where she bases upon her experience in finance.
  • Surveys and sentiment analysis for user insights where she rests on her academic experience.
  • Network security, including firewalls, firewall management, and orchestration where she applies her industry analysis experience.

Professional experience

Ezgi worked both in academia and the industry before:
  • Çankaya University as Part-time Teaching Staff
  • TED Ankara College as Education Support Specialist
  • TED University as Teaching Assistant
  • AKFEN Holding Inc. as Finance Specialist

Education

Graduated with a PhD. from the Department of Business and Administration at Bilkent University.

Academic publications

  • Arslan E. and Tanyeri-Günsür B. (2025). Ambitious sons and understanding daughters: investor perceptions of gender and the valuation of family firms". Gender in Management: An International Journal, 1-22, DOI: 10.1108/GM-11-2024-0636.
  • Alp, E. (2024). An Examination of Factors in Financial Asset Valuation. Nişantaşı Üniversitesi Sosyal Bilimler Dergisi, 12 (Special Issue), 60-72. DOI: 52122/nisantasisbd.1467788.
  • Tanyeri A. B., and Alp E. (2023). Law as an external governance mechanism: valuation of family firms in countries with differing judicial protection of shareholder rights. Corporate Governance: An International Review, 1-22, DOI: 10.1111/corg.12484.

Conference presentations

Latest Articles from Ezgi

AIJul 9

Top 4 Methods of Sentiment Analysis in Retail Industry ['26]

In 2022, the retail industry surpassed $5 trillion for the first time, indicating a continuing desire to buy and consume.However, meeting an increasing number of customers’ needs, and standing out among competitors require great effort. That’s why retail companies have started to automate their processes to benefit from AI-powered methods even more.

AIJul 9

Top 7 Sentiment Analysis Challenges in 2026

Words are the most powerful tools to express our thoughts, opinions, intentions, desires, or preferences. However, the complexity of human languages constitutes a challenge for AI methods that work with natural languages, such as sentiment analysis. Explore sentiment analysis challenges and ways to improve sentiment analysis accuracy: Top 7 challenges in sentiment analysis 1.

Enterprise SoftwareJul 3

Digital Transformation and Sustainability: Top 5 Digital Solutions

The World Economic Forum (WEF) identifies climate change and environmental issues as the greatest threats to the global economy. My academic experience on sustainability practices points that embracing digital transformation and sustainability initiatives are strategic actions executives can take to move toward a more sustainable future.

AIJun 25

Sentiment Analysis Machine Learning: Approaches & 5 Examples

It is not surprising that the use of AI in the workplace has increased by 270% from 2015 to 2019, considering the data available and its exponential growth.

Enterprise SoftwareJun 24

Layers & Components of IoT Architecture

Though businesses are investing in IoT, buyers may not be clear about all the components that they need to invest in.

DataJun 19

30 Market Research Stats from Reputable Sources in 2026

Venturing into the evolving sphere of market research, the article uncovers a range of key statistics that capture the sector’s state and trends. It’s a deep dive into how market dynamics are being reshaped, highlighting leading role of the U.S.

DataJun 16

Traditional vs. Online Survey Research in 2026

Conducting survey research helps businesses collect data from customers, employees, or the public. Collecting data with traditional methods, such as paper-pencil or telephone, is costly, time-consuming, and cannot keep up with the digitally transforming world. Thanks to online survey research tools, businesses can quickly reach a broad audience’s opinion and make necessary adjustments.

AIJun 10

Top 7 Open Source Sentiment Analysis Tools

Text analytics is estimated to exceed a global market value of US$ 56 billion by 2029. Sentiment analysis has gained worldwide momentum as one of the text analytics applications. Businesses that have not implemented sentiment analysis may feel an urge to find out the best tools and use cases for benefiting from this technology.

AIJun 10

Top 7 Examples of ChatGPT Sentiment Analysis

A study estimated that 80% of companies will adapt to solutions  that utilize sentiment analysis in 2023. Sentiment analysis is a Natural Language Processing (NLP) method that classifies texts, images, or videos based on the emotional tone as negative, positive, or neutral.

AIJun 2

Top 10+ Emotional AI Examples & Use Cases

The emotion detection and recognition (EDR) market is estimated to reach at ~$50 Bn in 2024, and is expected to reach ~$173 Bn by 2031. Emotion detection and recognition rely on emotion AI to identify, process, and simulate human feelings and emotions.