Abstract
Social Media has increasingly acquired enormous storehouses of shared interactive ideas among people in virtual communities over the past decade. While considering hot topics in social media as the culture of today’s world, related analysis derived from its trend allows researchers and society understand public point of view regarding emerging topics through online social interactions. The ease of categorizing the trends of topics makes it beneficial to find how people react to a certain topic. In our research, the distributions of keywords from hot topics are studied. First of all, a private cloud system is set up to collect and to filter raw data from social network (Twitter). Then, a web-based dashboard is developed to demonstrate static numbers and related charts. Some experiments are performed based on the newly-developed system deployed. Distribution functions of keywords are studied based on 2016 data, and further applications are applied based on 2017 spring data. Further cross comparisons are deployed based on daily, weekly, and monthly frequencies from different locations.
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Liu, Y., Xu, W. (2020). A Cloud-Based Dashboard for Time Series Analysis on Hot Topics from Social Media. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1075. Springer, Cham. https://doi.org/10.1007/978-3-030-32591-6_36
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DOI: https://doi.org/10.1007/978-3-030-32591-6_36
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