Application of sentiment analysis for information overload detection in an Ecommerce competitive environment
Abstract: This master thesis is focusing on the information overload in digital marketing and using the method of sentiment analysis to detect if the issue occurs or not. A model and method of different sentiments (positive and negative) were organized, and evaluated based on the statistical and prominent findings of the emotional value in the customer satisfaction in online reviews. Findings were analyzed, as to what data, and categories showed value which proved information overload and these were thereafter connected to previous academic studies of sentiment analysis and customer satisfaction connected to information overload. The results of the analysis proved that the sentiment analysis had significance in some aspects and categories to combat the information overload issue in digital marketing for online consumers.
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