4,247 research outputs found
Ridgecrest California Earthquake Twitter Data
No full textDataset Metrics
Number of objects (submissions): 1,363,924
Start Date: Sat Jul 06 03:19:53 +0000 2019
End Date: Sat Jul 06 03:25:27 +0000 2019
Format: csv
Overview
This dataset contains tweet ids for a five minute time span starting at the beginning of the 7.1 magnitude Ridgecrest earthquake.
Methodology
This data was compiled using the methodology detailed here.
The Twitter ids can be rehydrated using Twitter's "statuses lookup" endpoint. Twitter TOS prevents including the actual tweets. However, please feel free to contact the author of this publication if you need further assistance or access to the original data (for academic research purposes only). When collecting the data, the following sequence numbers were used: 0,1,2,3,4,5,6,7,8,9. The machine ids in rotation during this time span were: 341, 322, 327, 332, 334, 335, 336, 326, 321, 382, 366, 378, 364, 374, 373, 361, 333, 363, 377, 379.
This represents a 99% (±0.5%) sample rate of the full population of publicly available tweets during the time span for this data set.
Contact
If you have any questions about the data or require more details on the methodology, you are welcome to contact the author
Ridgecrest California Earthquake Twitter Data
No full textDataset Metrics
Number of objects (submissions): 1,363,924
Start Date: Sat Jul 06 03:19:53 +0000 2019
End Date: Sat Jul 06 03:25:27 +0000 2019
Format: csv
Overview
This dataset contains tweet ids for a five minute time span starting at the beginning of the 7.1 magnitude Ridgecrest earthquake.
Methodology
This data was compiled using the methodology detailed here.
The Twitter ids can be rehydrated using Twitter's "statuses lookup" endpoint. Twitter TOS prevents including the actual tweets. However, please feel free to contact the author of this publication if you need further assistance or access to the original data (for academic research purposes only). When collecting the data, the following sequence numbers were used: 0,1,2,3,4,5,6,7,8,9. The machine ids in rotation during this time span were: 341, 322, 327, 332, 334, 335, 336, 326, 321, 382, 366, 378, 364, 374, 373, 361, 333, 363, 377, 379.
This represents a 99% (±0.5%) sample rate of the full population of publicly available tweets during the time span for this data set.
Contact
If you have any questions about the data or require more details on the methodology, you are welcome to contact the author
Twitter Tweets for Donald J. Trump (@realdonaldtrump)
No full textDataset Metrics
Total size of data uncompressed:115901693 bytes
Number of objects (submissions): 40,241
Start Date: Mon May 04 18:54:25 +0000 2009
End Date: Thu Jul 11 15:52:19 +0000 2019
Format: ndjson (new line delimited JSON)
Overview
This dataset contains all known publicly available tweets for Donald J. Trump's (@realdonaldtrump) Twitter account.
Methodology
This data was compiled from multiple sources including several online Github accounts that contained the status ids for previous tweets made by Donald Trump. All ids were compiled into a single list and then those ids were requested from Twitter's "statuses lookup" endpoint. Tweets deleted by Donald Trump will not be in this dataset but can be obtained from the author of this publication for a subset of the time range present in this dataset. This dataset will also include the tweet information for any retweeted tweets under the "retweeted_status" key for each JSON object. The user object has been left in each tweet (both the main tweet and retweeted / quoted tweets if they exist).
Contact
If you have any questions about the data or require more details on the methodology, you are welcome to contact the author
Twitter Tweets for Donald J. Trump (@realdonaldtrump)
No full textDataset Metrics
Total size of data uncompressed:115901693 bytes
Number of objects (submissions): 40,241
Start Date: Mon May 04 18:54:25 +0000 2009
End Date: Thu Jul 11 15:52:19 +0000 2019
Format: ndjson (new line delimited JSON)
Overview
This dataset contains all known publicly available tweets for Donald J. Trump's (@realdonaldtrump) Twitter account.
Methodology
This data was compiled from multiple sources including several online Github accounts that contained the status ids for previous tweets made by Donald Trump. All ids were compiled into a single list and then those ids were requested from Twitter's "statuses lookup" endpoint. Tweets deleted by Donald Trump will not be in this dataset but can be obtained from the author of this publication for a subset of the time range present in this dataset. This dataset will also include the tweet information for any retweeted tweets under the "retweeted_status" key for each JSON object. The user object has been left in each tweet (both the main tweet and retweeted / quoted tweets if they exist).
Contact
If you have any questions about the data or require more details on the methodology, you are welcome to contact the author
Reddit May 2019 Submissions
No full textDataset Metrics
Total size of data uncompressed: 59,515,177,346 bytes
Number of objects (submissions): 19,456,493
Reddit API Documentation: https://www.reddit.com/dev/api/
Overview
This dataset contains all available submissions from Reddit during the month of May, 2019 (using UTC time boundaries). The data has been split to accommodate the file upload limitations for dataverse. Each file is a collection of json objects (ndjson). Each file was then compressed using zstandard compression (https://facebook.github.io/zstd). The files should be ordered by the id of the submission (represented by the id field). The time that each object was ingested is recorded in the retrieved_on field (in epoch seconds).
Methodology
Monthly Reddit ingests are usually started around a week into a new month for the previous month (but could be delayed). This gives submission scores, gildings and num_comments time to "settle" close to their eventual score before Reddit archives the posts (usually done after six months from the post's creation).
All submissions are ingested via Reddit's API (using the /api/info endpoint). This is a "best effort" attempt to get all available data at the time of ingest. Due to the nature of Reddit, subreddits can go from private to public at any time, so it's possible more submissions could be found by rescanning missing ids.
The author of this dataset highly encourages any researchers to do a sanity check on the data and to rescan for missing ids to ensure all available data has been gathered. If you need assistance, you can contact me directly.
All efforts were made to capture as much data as possible. Generally, > 95% of all ids are captured. Missing data could be the result of Reddit API errors, submissions that were private during the ingest but then became public and subreddits that were quarantined and were not added to the whitelist before ingesting the data. When collecting the data, two scans are done. The first scan of ids using the /api/info endpoint collects all available data. After the first scan, a second scan is done requesting only missing ids from the first scan. This helps to keep the data as complete and comprehensive as possible.
Contact
If you have any questions about the data or require more details on the methodology, you are welcome to contact the author
Reddit May 2019 Submissions
No full textDataset Metrics
Total size of data uncompressed: 59,515,177,346 bytes
Number of objects (submissions): 19,456,493
Reddit API Documentation: https://www.reddit.com/dev/api/
Overview
This dataset contains all available submissions from Reddit during the month of May, 2019 (using UTC time boundaries). The data has been split to accommodate the file upload limitations for dataverse. Each file is a collection of json objects (ndjson). Each file was then compressed using zstandard compression (https://facebook.github.io/zstd). The files should be ordered by the id of the submission (represented by the id field). The time that each object was ingested is recorded in the retrieved_on field (in epoch seconds).
Methodology
Monthly Reddit ingests are usually started around a week into a new month for the previous month (but could be delayed). This gives submission scores, gildings and num_comments time to "settle" close to their eventual score before Reddit archives the posts (usually done after six months from the post's creation).
All submissions are ingested via Reddit's API (using the /api/info endpoint). This is a "best effort" attempt to get all available data at the time of ingest. Due to the nature of Reddit, subreddits can go from private to public at any time, so it's possible more submissions could be found by rescanning missing ids.
The author of this dataset highly encourages any researchers to do a sanity check on the data and to rescan for missing ids to ensure all available data has been gathered. If you need assistance, you can contact me directly.
All efforts were made to capture as much data as possible. Generally, > 95% of all ids are captured. Missing data could be the result of Reddit API errors, submissions that were private during the ingest but then became public and subreddits that were quarantined and were not added to the whitelist before ingesting the data. When collecting the data, two scans are done. The first scan of ids using the /api/info endpoint collects all available data. After the first scan, a second scan is done requesting only missing ids from the first scan. This helps to keep the data as complete and comprehensive as possible.
Contact
If you have any questions about the data or require more details on the methodology, you are welcome to contact the author
Jason Bond Family History
No full textJason Bond authored this family history as part of the course requirements for HIST 550/700 Your Family in History offered online in Fall 2017 and was submitted to the Pittsburg State University Digital Commons. Please contact the author directly with any questions or comments: [email protected]
Jason vs GIJOE
No full textThesis (Master's)--University of Washington, 2019Jason vs GI JOE is partly an exercise in autobiography, an experiment in relational aesthetics, and an interdisciplinary artist project at the intersection of comic books, creative writing and performance art. This comic book, Jason vs. GIJOE, is a postmodern double erasure, based on the comic book GIJOE: Cobra II (Issue 1). The original pictures from the comic book have been removed, and replaced by a series of short narratives, describing autobiographical events from the life of the author: me, Jason. Speech bubbles from the original have been left to comment back over top of the stories, obscuring meaning but creating moments of unplanned dialogue. The comic is a readymade, twice erased: once to replace the drawings of the initial comic, and again when using the original dialogue bubbles to speak back to the narrative
Oral history interview with Jason Poudrier
No full textJason Poudrier, author, discusses growing up in a military family and living in Alaska, North Dakota, Oregon, and finally Oklahoma. He describes what it was like enlisting in the Army after high school in 2001 and how his military service affected him. A recipient of the Purple Heart, he shares his experiences getting injured by shrapnel in Iraq. He later talks about how he uses poetry and writing to cope with his memories of war, and how he hopes to help others do the same.The Deep Roots: Oklahoma Authors Collection is a series of interviews with authors who discuss their lives, work, and creative processes
Lynn Brunelle and Jason Chin: Cook Prize 2025, Gold Medal Acceptance Speech
No full textAuthor Lynn Brunelle and illustrator Jason Chin give an acceptance speech for Life After Whale: The Amazing Ecosystem of a Whale Fall (Neal Porter Books/Holiday House)https://educate.bankstreet.edu/cook/1016/thumbnail.jp
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