Social media has become a vital part of social life. It affects the beliefs, values, and attitudes of people, as well as their intentions and behaviors. Meanwhile, social media enables governments and organizations to engage people while allowing consumers to make informed decisions. Therefore, converting social media content into information, key concepts, and themes is crucial for generating knowledge and formulating strategies. In this paper, we introduce a grounded theory approach that involves (i) defining the goal and scope of a study; (ii) logically and systematically identifying social media sources, total sample size, and the sample size of every source category; (iii) employing computer-aided lexical analysis with statistical and graphical methods to identify the key dimensions of the topic while minimizing human errors, as well as coding and categorization biases; and (iv) interpreting the findings of the study. This systematic approach was illustrated with the destination image of Macao as an example. The proposed methodology with its hybrid nature can quantitatively analyze qualitative social media content (e.g., impressions, opinions, and feelings) and can identify emergent concepts from the ground up. This paper contributes to electronic commerce research by presenting a novel approach for extracting, analyzing, and understanding social media content.