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Automatic Identification and Classification of Bragging in Social Media ...
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Machine Extraction of Tax Laws from Legislative Texts
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In: Proceedings of the Natural Legal Language Processing Workshop 2021 (2021)
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Point-of-Interest Type Inference from Social Media Text ...
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Abstract:
Physical places help shape how we perceive the experiences we have there. For the first time, we study the relationship between social media text and the type of the place from where it was posted, whether a park, restaurant, or someplace else. To facilitate this, we introduce a novel data set of $\sim$200,000 English tweets published from 2,761 different points-of-interest in the U.S., enriched with place type information. We train classifiers to predict the type of the location a tweet was sent from that reach a macro F1 of 43.67 across eight classes and uncover the linguistic markers associated with each type of place. The ability to predict semantic place information from a tweet has applications in recommendation systems, personalization services and cultural geography. ... : Accepted at AACL-IJCNLP 2020 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences; Social and Information Networks cs.SI
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URL: https://arxiv.org/abs/2009.14734 https://dx.doi.org/10.48550/arxiv.2009.14734
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Fact vs. Opinion: the Role of Argumentation Features in News Classification ...
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The Remarkable Benefit of User-Level Aggregation for Lexical-based Population-Level Predictions ...
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