Analyzing Product Usage Based on Twitter Users Based on Datamining Process
S. Umamaheswari, K. Harikumar · 2020 International Conference on Computation, Automation and Knowledge Management (ICCAKM) · 2020
This paper further enhances the techniques and chronological methods in order to perform the corresponding manipulation and further prediction analysis. We have acquired a real time dataset based on the twitter user's comments sections. The uniqueness of the dataset is that we have extracted only the particular comments which syntheses a particular word based on the product. Then further repetitive extraction is made in order to complete the dataset. Our dataset has three columns based on the ideology that the particular user or our focused subject has enhanced any detail about the product that we are observing. In this precise dataset we have taken the subject about the products usage by the users that have been manufactured by the companies Google and Apple. Both technology giants have well versed their technology reign in this era and their further focused in their upcoming cyber projects and their products will be more advanced in future. As they are in involved in further optimization in their devices and increasing their specifications. It would be complex task to accomplish their project without the feedback, pros and cons of their predecessor projects. They can extract such features from twitter api dataset and they could further enhance their product. They could analyze the drawback, whether the product has reached the market and came out with success all type of this information can be extracted from social media instead of conducting a survey. Such process would be more hectic classification and we cannot predict any accurate results. So we proceed with the social media Data mining Process.