The rule-based method is useful for analyzing online consumer reviews. The performance can be improved by recognizing different types of features and designing methods accordingly. For product feature extraction, subjective feature-oriented methods perform better than objective feature-oriented methods. Direct dependency relation and review-specific patterns resulted in best recall in each category. The generality of rule-based methods can be approached by developing domain-independent rules and pruning strategies.