Clickbait Identification in Social Media Text using LSTM based Approach

Capsule networks can also be used to investigate the working under the input of text data rather than images. Such limitations where taken into account while identifying clickbaits in the usage of texts from social media. Several systems in existing work focus on usage of Long Term Short Memory (LSTM) approach to identify clickbaits. Due to certain disadvantages, the issue was considered as research focus area. The proposed system utilizes three-layered architecture where the first layer takes the input as text. After vectorization, the input is categorized and the final layer produces the output. The layered architecture also takes lesser response time thereby making the system efficient which is showcased in the experimental results obtained after implementation.