QUAD DATASET

India is known for its highly disciplined foreign policies, strategic location, vibrant and massive Diaspora. India envisages enhancing its scope of cooperation, trade and widens its sphere of relations with the Pacific. As a result, the world is witnessing the rise of Indo-Pacific ties. Before the 1980’s the keystone of the universe was called the Atlantic, but now a radical shift to the east is noticed by the term “Indo-Pacific‟. In this respect, a recent development occurred as a partnership, the Malabar exercise, in the waters of the Pacific and the Indian Oceanic region, which supports and proclaim free, open, and comprehensive Indo-Pacific and stays committed on a rule-based order. Considering the mass inclusion of people on social media platforms and contemplating their opinion has been of much interest in the research. Understanding and categorizing a large dataset of ideas into positive, negative, and neutral aspects is challenging. Our motive is to elucidate how the world, especially the citizens, is welcoming this strategic and influencing partnership. Also, Could social media influence the meaning of partnership? Our paper is divided into two aspects, one dealing with the comparison of various techniques and the other telling opinions of people regarding Indo-pacific relations. We used a geo-specific dataset obtained in various languages. Also, we applied a blend of various ML and DL techniques, feature extraction models, and opinion-based classification, which not only gives an analysis of opinions regarding “Indo-pacific” but also provides an in-depth insight to the comparison of various state-of-the-art sentiment analysis techniques, which is provided as a continuation of earlier review presented on sentiment analysis. The word-cloud visualization system assists people in understanding the changes of public sentiment reactions better.

Related to above sarch keywords following tweets were extracted b/w 15 nov 2020 to 10 jan 2021

29499  English TWEETS extracted,

4628 Japanese tweets extracted

678 Hindi tweets extracted 

CODE LINK: MAJOR-PROJECT-QUAD/QUAD_MAIN_CODE.ipynb at main · divyansh0608/MAJOR-PROJECT-QUAD (github.com)

IEEE PAPER LINK: https://ieeexplore.ieee.org/document/9441772