  Social media has gained an immense popularity over the last decade. People
tend to express opinions about their daily encounters on social media freely.
These daily encounters include the places they traveled, hotels or restaurants
they have tried and aspects related to tourism in general. Since people usually
express their true experiences on social media, the expressed opinions contain
valuable information that can be used to generate business value and aid in
decision-making processes. Due to the large volume of data, it is not a
feasible task to manually go through each and every item and extract the
information. Hence, we propose a social media analytics platform which has the
capability to identify discussion pathways and aspects with their corresponding
sentiment and deeper emotions using machine learning techniques and a
visualization tool which shows the extracted insights in a comprehensible and
concise manner. Identified topic pathways and aspects will give a decision
maker some insight into what are the most discussed topics about the entity
whereas associated sentiments and emotions will help to identify the feedback.
