For me, the opioid crisis is more than a national headline. I come from a small town in Monroe, Michigan that has been devastated by this epidemic. My neighbors and family friends have lost their…
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Some shareholders of a major drug distributor are arguing that the company's goals should be more in line with society's.
In the nearly 20 years since I became director of the Drug Enforcement Administration, the illegal use of prescription drugs has become an epidemic that our nation couldn’t have imagined. Drug addiction is an insidious enemy of our families and our nation. ...
A blog on creativity, in our schools and in the workplace. Also devoted to fighting addiction in every way possible.
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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