Data

Australian Twitter Dataset 2019-20

Adelaide University
Mitchell, Lewis
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25909/33283899.v1&rft.title=Australian Twitter Dataset 2019-20&rft.identifier=10.25909/33283899.v1&rft.publisher=Adelaide University&rft.description=This dataset comprises object IDs for tweets filtered from the Twitter gardenhose (10%) feed from calendar years 2019-20, originating from Australian accounts. By this we mean, tweets from accounts with a location field or profile description that contains one or more of the following strings: `australia',`adelaide', `perth',`melbourne', `darwin', `launceston', `hobart', `canberra', `sydney', `brisbane', `cairns', `wollongong', `geelong', `townsville', `toowoomba', `ballarat', `victoria', `queensland', `tasmania', `bendigo',`wodonga', `gold coast', `sunshine coast', `tweed heads', `queanbeyan', `maitland', `nsw', `qld’. This list of strings was derived from a list of the largest Australian cities, towns and regions by population, as well as common state and territory names and abbreviations. It is not exhaustive, and it is recognised that the dataset contains tweets from non-Australian accounts, e.g., Victoria in Canada. This dataset does not utilise geolocation metadata.Note that the dataset contains tweet IDs only, not the tweets themselves, and some tweets may have been deleted.&rft.creator=Mitchell, Lewis &rft.edition=1&rft_rights= https://creativecommons.org/licenses/by/4.0/&rft_subject=Graph, social and multimedia data&rft_subject=Data engineering and data science&rft_subject=Data mining and knowledge discovery&rft_subject=Complex systems&rft_subject=Applied statistics&rft_subject=Statistical data science&rft_subject=Tweets Dataset&rft_subject=Twitter&rft_subject=Social Media&rft_subject=text and context&rft.type=dataset&rft.language=English Access the data
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Full description

This dataset comprises object IDs for tweets filtered from the Twitter gardenhose (10%) feed from calendar years 2019-20, originating from "Australian" accounts. By this we mean, tweets from accounts with a location field or profile description that contains one or more of the following strings:

`australia',`adelaide', `perth',`melbourne', `darwin', `launceston', `hobart', `canberra', `sydney', `brisbane', `cairns', `wollongong', `geelong', `townsville', `toowoomba', `ballarat', `victoria', `queensland', `tasmania', `bendigo',`wodonga', `gold coast', `sunshine coast', `tweed heads', `queanbeyan', `maitland', `nsw', `qld’.

This list of strings was derived from a list of the largest Australian cities, towns and regions by population, as well as common state and territory names and abbreviations. It is not exhaustive, and it is recognised that the dataset contains tweets from non-Australian accounts, e.g., Victoria in Canada. This dataset does not utilise geolocation metadata.

Note that the dataset contains tweet IDs only, not the tweets themselves, and some tweets may have been deleted.

This dataset is part of a larger collection

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Subjects
Applied statistics | Complex systems | Data engineering and data science | Data mining and knowledge discovery | Graph, social and multimedia data | Social Media | Statistical data science | Tweets Dataset | Twitter | text and context |

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Identifiers
ACN 633 798 857