This paper introduces an innovative approach for assessing visitor satisfaction at the destination level by identifying attributes of interest from social media text and indirectly measuring performance and importance values. A lexicon-based method for sentiment analysis is applied to determine performance value at the destination level, while importance is calculated using an adjusted association rule mining algorithm. The results are validated with earlier survey-based attributes relevant to visitors and Australia's case. The results demonstrate encouraging accuracy, suggesting that the proposed methodology offers opportunities to assess tourist satisfaction at destinations with larger sample sizes for a lower cost and greater data collection flexibility than traditional approaches. The methods proposed could be beneficial in a wide range of tourism contexts.