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arxiv: 1810.03067 · v1 · submitted 2018-10-07 · 💻 cs.IR · cs.CL

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Geocoding Without Geotags: A Text-based Approach for reddit

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classification 💻 cs.IR cs.CL
keywords redditdatageolocationinferencemodelsacrossapproachtext-based
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In this paper, we introduce the first geolocation inference approach for reddit, a social media platform where user pseudonymity has thus far made supervised demographic inference difficult to implement and validate. In particular, we design a text-based heuristic schema to generate ground truth location labels for reddit users in the absence of explicitly geotagged data. After evaluating the accuracy of our labeling procedure, we train and test several geolocation inference models across our reddit data set and three benchmark Twitter geolocation data sets. Ultimately, we show that geolocation models trained and applied on the same domain substantially outperform models attempting to transfer training data across domains, even more so on reddit where platform-specific interest-group metadata can be used to improve inferences.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Reddit's Globalization over Twenty Years: Inferring Community Time Zone from Activity Timestamps

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    A 4 a.m. activity minimum heuristic infers community time zones from timestamps with sub-hour accuracy on Reddit, enabling scalable analysis of the platform's globalization without user location data.