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Nanotweets
Nanotweets
Nanotweets
Nanotweets
Nanotweets
Nanotweets
Nanotweets
Nanotweets
Nanotweets
Nanotweets
Nanotweets
Nanotweets
Nanotweets
Nanotweets
Nanotweets
Nanotweets
Nanotweets
Nanotweets
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Nanotweets

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We believe open annotation is a unique new capability that has the potential to radically transform the way we engage with scientific content across the web. Not only annotations are central in the …

We believe open annotation is a unique new capability that has the potential to radically transform the way we engage with scientific content across the web. Not only annotations are central in the realization of the web of documents by facilitating the formalization and discovery of relations across papers. Most importantly, annotations, we argue, are central in the empowerment of communities of practices by making content based conversations possible. In addition, the activity arising from such content based exploration allows for the definition of a novel alternative metric. As the annotation is specific to a part of the text, it allows for granular analysis of the paper; such metric tells us not just the number of tweets or LIKEs for a given document. It also allows us to identify the topics that are arising interest and how are these being discussed. The contribution is therefore twofold; on the one hand NanoTweets are a type of community based annotation, on the other, hand, NanoTweets are also delivering a granular metric rooted within the content of the document -simplifying content based business intelligence.

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  • 1. NanoTweets.com Alexander Garcia, PhD Similarly to the general Web, specialized information will demand specialized sharing and discovery tools in support of social aspects for targeted communities.
  • 2. Why? • • • • Micro content analytics Promoting specifics Supporting conversations Making efficient use of Social Networks, not just Twitter • Social Engagement • Influencers, topics and persons • Adding value to content and social participation
  • 3. A simple example • Users annotate with no limitations; underneath, the tool does semantic annotation, generates an URI per annotation, the annotated text is trimmed and shared over social networks. The entire annotation, the corresponding social activity it generates, the metadata for the publication, provenance, etc. is RDFised and shared over a triplet store.
  • 4. A new ALM • Facebook, Tweeter, Google+, Blogs, etc. are about a URI as a whole • What is interesting in the paper? • What are the hot topics within the paper? • Mostly available over web based aggregators • Nanotweets are about specifics in the document • NanoTweets are granular semantic facts about specifics within the paper • The conversation is the aggregator
  • 5. ALMs in the News • ALMs have been in the news for quite a long time
  • 6. ALM as a simple aggregator issue
  • 7. ALM as a simple aggregator issue
  • 8. ALM as a simple aggregator issue
  • 9. NanoTweets complementing ALMs • Nanopublications + tweeter within scholarly communication • Specifics in the paper • Topic analysis
  • 10. In Action A Meta-Analytic Review of Prospective Memory and Aging Supporting multiple formats and devices http://psycnet.apa.org/jour nals/pag/19/1/27.html Moreover, the present results provide clear evidence that at least some PM tasks do not place such heavy demands on effortful or executive processes as has been presumed and are thus not subject to disproportionate age-related decline. EBPM tasks that imposed lowstrategic demands according to McDaniel and Einstein’s (2000) multiprocess framework were associated with significantly smaller age effects than EBPM tasks that imposed relatively highstrategic demands. Entity Recognition =140 Chars #nanotweets # elderly population erroneous to regard all tests of PM and particularly EBPM as tests that draw heavily on self-initiated retrieval Everything >140 Chars NLP and Semantic Processing goes to our triplet store, available via API, knowledge is enhanced and characterized. Social activity is followed #nanotweets # Memory and Aging some PM tasks dont place heavy demands on effortful or executive processes
  • 11. In Action http://www.biomedcentral.com/1471-2407/13/400 PDF, ePUB, Mobile It has recently been reported that patients who were administered hyperthermic IP chemotherapy (DOX in combination with cisplatin ) following surgical debulking of peritoneal MMs had an increased 5 year survival rate of 29-63% . We know key knowledge, NanoTweets NLP
  • 12. In action It has recently been reported that patients who were administered hyperthermic IP chemotherapy (DOX in combination with cisplatin) following surgical debulking of peritoneal MMs had an increased 5 year survival rate of 29-63% . NanoTweets >140 chrs =140 chrs User Generated NanoTweet NLP and Semantic Processing #nanotweets #cancer increased 5 year survival rate of 29-63% administering hyperthermic IP chemotherapy Nanotweet hashtag User generated hashtag #nanotweets #cancer increased 5 year survival rate of 29-63% administering hyperthermic IP chemotherapy
  • 13. In action It has recently been reported that patients who were administered hyperthermic IP chemotherapy (DOX in combination with cisplatin) following surgical debulking of peritoneal MMs had an increased 5 year survival rate of 29-63% . NanoTweets >140 chrs =140 chrs User Generated NanoTweet Nanotweet hashtag NLP and Semantic Processing #nanotweets #cancer increased 5 year survival rate of 29-63% administering hyperthermic IP chemotherapy User generated hashtag #nanotweets #cancer increased 5 year survival rate of 29-63% administering hyperthermic IP chemotherapy We store everything, original text, provenance, tweet, retweets, etc. We also get DOI information for the paper at hand and available metrics; in addition, when possible we enhance the knowledge for the selected text based on semantic resources like
  • 14. Nanotweet model Nanotweet Tweet elements Provenance rdf:type hashtag Tiny URL prov:wasAttributedTo hasHashtag owl:sameAs Nanotweet RDFizator agent dcterms:creator dcterms:created prov:generatedAtTime Selected text prov:wasGeneratedBy Date & time Tweeter account cnt:chars Plain text hasAnnotation Links to publication dcterms:references Publisher URL DOI Nanotweet RDF dataset void:inDataset One annotation for each entity recognized in the selected text pav:createdOn ao:annotatesResource Topics pav:createdBy Annotation Ontological term pav:authoredBy Annotator Agent ao:hasTopic Occurrences in selected text rdf:type Term in text biotea:occurrences ao:body aot:ExactQualifier Nanotweet data Web link External data number
  • 15. So… • Allows us to discover hot trends based on micro content • Retarget, we know true interests from the community • Continuous generation of nanopublications • Solves nanopublication entry curve • Allows us to make a different use of social networks • Consistent User Experience • Traceable across formats –PDF, ePUB, HTML
  • 16. Thanks • Wanna NanoTweet?

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