Abstract
The public often relies on social media to discuss and organize activities such as rallies and demonstrations. Monitoring and analyzing open-source social media platforms can provide insights into the locations and scales of rallies and demonstrations, and help ensure that they are peaceful and orderly.
This chapter describes a dictionary-based, semi-supervised learning methodology for obtaining location information from Chinese web forums. The methodology trains a named entity recognition model using a small amount of labeled data and employs n-grams and association rule mining to validate the results. The validated data becomes the new training dataset; this step is performed iteratively to train the named entity recognition model. Experimental results demonstrate that the iteratively-trained model has much better performance than other models described in the research literature.
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Qin, S., Wen, Q., Chow, KP. (2021). PREDICTING THE LOCATIONS OF UNREST USING SOCIAL MEDIA. In: Peterson, G., Shenoi, S. (eds) Advances in Digital Forensics XVII. DigitalForensics 2021. IFIP Advances in Information and Communication Technology, vol 612. Springer, Cham. https://doi.org/10.1007/978-3-030-88381-2_9
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DOI: https://doi.org/10.1007/978-3-030-88381-2_9
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