Identification of Negative Intent in Social Media Posts Using Natural Language Processing

Daily content viewing and/or posting on social media is very common and influences people across all geographies using numerous strategies and ways. A number of daily activities over web platforms like YouTube in terms of posting, watching, and commenting on videos. This is a report that contains a quickly expanding number of online channels where users post, jot down, and comment on a wide range of topics. NLP is applied to quickly take information from online or web content, that will facilitate your business in very different and numerous ways. Customer-specific data can be easily extracted using NLP, and this data can then be used to create advertising campaigns that are specifically targeted to your customers. This assists in introducing your company to the appropriate target market, which is more likely to convert. The paper will perform the critical analysis of versatile methodologies adapted by various researchers for negative intent identification in social networking sites. The paper will also try to observe the challenges associated with the same. This paper will also analyze the usage of NLP in identifying the negative intent in social media posts.