Archive-It Collection 649: Tragedy at Virginia Tech Web Archive, 2007-2012
We Remember: Biographies | Virginia Tech
Families have approved and released these official biographies and photos of our 32 fallen Hokies. Please join us in remembering and honoring their lives by clicking on their names or photos. The u...
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In the hours following the April 16 tragedy, the student-driven volunteer organization Hokies United placed 32 Hokie Stones on the Drillfield. The semi-circle of stones became a place to gather, to...
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The Latest News and Notices | Virginia Tech
The Latest News and Notices This page is being updated regularly by University Relations. Please check back often for updates and additional information. Media notice: media truck guidelin...
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BLACKSBURG, Va., Aug. 22, 2007 – On May 9, 2007, Virginia Tech President Charles Steger directed three internal reviews in the wake of the April 16 tragedy on the Virginia Tech campus. He directed ...
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On April 16, 2009, Virginia Tech will remember the vibrant lives of 32 students and faculty who were tragically taken from their loved ones and our community. Through reflection, spoken word, music...
This story was constructed automatically by using an updated version of AlNoamany's Algorithm. For more information about how this algorithm was developed, how it works, and its evaluation, please consult:
- Y. AlNoamany, M. C. Weigle, and M. L. Nelson, "Generating Stories From Archived Collections," in Proceedings of the 2017 ACM on Web Science Conference, pp. 309–318, ACM Press, 2017. https://doi.org/10.1145/3091478.3091508.
- Y. AlNoamany, M. C. Weigle, and M. L. Nelson, " Stories From the Past Web," Tech. Rep. 1705.06218, May, 2017. https://arxiv.org/abs/1705.06218.
We employed the DSA toolkit to tell this story with the following steps.
- Hypercane selected the resources and generated the metadata for the story:
- It first executed AlNoamany's Algorithm:
- Discovered the Memento TimeMaps for the collection
- Analyzed these TimeMaps and reported the memento URI-Ms that were on-topic
- Filtered the content of those URI-Ms to find non-duplicates
- Filtered the content of those URI-Ms to find English language documents
- Sliced the collection by memento-datetime
- Clustered the mementos in each slice by Simhash distance
- Ranked the mementos in each cluster by a ranking equation
- Filtered each cluster for the highest ranking mementos
- Ordered each memento by publication date
- It used Archive-It Utilities to extract all metadata from the collection, such as who created the collection and the collection's name
- It analyzed all mementos to automatically discover the most frequent sumgrams and named entities present in the overall story
- It analyzed all images in these mementos to automatically select the best image for the overall story
- It then formatted the data for the story based on all of this input
- Raintale took the input from Hypercane and rendered the final product with information supplied by MementoEmbed
