Search engines play an important role in providing us with the main information of our daily life. The research on the search behavior on the Internet enjoys greater and greater popularity, for the search behavior has been proved to affect our daily decisions in purchasing, traveling, and even defining beauty. However, there is still a lack of full appreciation of the relation between the search behavior itself in terms of the emotional meaning and the decisions thus generated. Therefore, this study was carried out to analyze the emotional meanings of 13,915 English words obtained from Google Trends and the profits gained from the US house market by automatic transactions and discovered that the emotional meanings of the search contents could modulate the financial decision with unsupervised machine learning methods.