Exploration of Competitive Market Behavior Using Near-Real-Time Sentiment Analysis

Inhaltsverzeichnis (Table of Contents)

• 1. Introduction
  • 1.1. Goal of the Thesis
  • 1.2. Chapter Outline
• 2. Sentiment Analysis
  • 2.1. Goals of Sentiment Analysis
  • 2.2. Use Cases of Sentiment Analysis
  • 2.3. Challenges of Processing Natural Language
    • 2.3.1. Negation
    • 2.3.2. Deontic Irrealis
    • 2.3.3. Languages
    • 2.3.4. Emoticons, Acronyms, and Further Improvements
  • 2.4. Domain-specific Language
  • 2.5. Algorithmic Principles of Sentimental Analysis
  • 2.6. Measuring Sentiment Analysis Accuracy
    • 2.6.1. Precision, Recall and Accuracy
    • 2.6.2. F-score
    • 2.6.3. Supervised Machine-Learning Algorithms

Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)

This master thesis explores the application of near-real-time sentiment analysis to understand competitive market behavior. The main objective is to analyze customer opinions in various markets using sentiment analysis, a tool for extracting emotions from text. The system is designed to be scalable for massive input directly from social networks and provides near-real-time results. Key themes include:

• Analyzing customer sentiment in various markets.
• Developing a scalable server architecture for sentiment analysis.
• Implementing commercial use cases for sentiment analysis.
• Examining the relationship between market maturity, emotional intensity, and company performance.

Zusammenfassung der Kapitel (Chapter Summaries)

• Chapter 1: Introduction This chapter introduces the thesis's goal, which is to utilize near-real-time sentiment analysis to understand competitive market behavior. It also provides an outline of the subsequent chapters.
• Chapter 2: Sentiment Analysis This chapter delves into the concept of sentiment analysis, exploring its goals, use cases, and challenges. It discusses specific challenges like negation, deontic irrealis, language variations, and emoticons/acronyms. The chapter also examines domain-specific language, algorithmic principles of sentiment analysis, and methods for measuring its accuracy.

Schlüsselwörter (Keywords)

This master thesis focuses on the analysis of competitive market behavior using near-real-time sentiment analysis. Key concepts include: sentiment analysis, market behavior, customer opinions, social networks, server architecture, commercial use cases, emotional intensity, market maturity, and company performance.