Social media is a forum where individuals congre gate and exchange information, thereby facilitating contemporary communication. Social media content presents unique challenges for information extraction due to its diverse and unstructured nature. For instance, the most prevalent content on social media platforms such as Twitter/X is commercial in nature, typically consisting of product advertisements or product promotions. The primary obstacle to accepting the information is the diverse and variable structure of the user’s writing styles, which present a variety of formats. The multitude of writing formats within the information in question renders it less efficient. This is where the role of information extraction comes in, transforming the unstructured information into a structured format using the Bidirectional Long-Short Term Memory with Conditional Ran dom Fields (BiLSTM-CRF) method. This method was selected because it provides context for information from both the past and the future, which is suitable