Advanced search
1 file | 461.32 KB

Adding meaning to Facebook microposts via a mash-up API and tracking its data provenance

Author
Organization
Abstract
The social networking website Facebook offers to its users a feature called ldquostatus updatesrdquo (or just ldquostatusrdquo), which allows users to create microposts directed to all their contacts, or a subset thereof. Readers can respond to microposts, or in addition to that also click a ldquoLikerdquo button to show their appreciation for a certain micropost. Adding semantic meaning in the sense of unambiguous intended ideas to such microposts can, for example, be achieved via Natural Language Processing (NLP). Therefore, we have implemented a RESTful mash-up NLP API, which is based on a combination of several third party NLP APIs in order to retrieve more accurate results in the sense of emergence. In consequence, our API uses third party APIs opaquely in the background in order to deliver its output. In this paper, we describe how one can keep track of provenance, and credit back the contributions of each single API to the combined result of all APIs. In addition to that, we show how the existence of provenance metadata can help understand the way a combined result is formed, and optimize the result combination process. Therefore, we use the HTTP Vocabulary in RDF and the Provenance Vocabulary. The main contribution of our work is a description of how provenance metadata can be automatically added to the output of mash-up APIs like the one presented here.
Keywords
meta data, application program interfaces, natural language processing, social networking (online), vocabulary

Downloads

  • 2011.10 - NWeSP 2011 - Thomas Steiner et al. - Adding Meaning to Facebook Microposts via a Mash-up API and Tracking Its Data Provenance.pdf
    • full text
    • |
    • open access
    • |
    • PDF
    • |
    • 461.32 KB

Citation

Please use this url to cite or link to this publication:

Chicago
Steiner, Thomas, Ruben Verborgh, Joaquim Gabarró Vallés, and Rik Van de Walle. 2011. “Adding Meaning to Facebook Microposts via a Mash-up API and Tracking Its Data Provenance.” In 2011 7th International Conference on Next Generation Web Services Practices, ed. Ajith Abraham, Emilio Corchado, Sang-Yong Han, Weisen Guo, Juan Corchado, and Athanasios Vasilakos, 342–345. Piscataway, NJ, USA: IEEE.
APA
Steiner, Thomas, Verborgh, R., Vallés, J. G., & Van de Walle, R. (2011). Adding meaning to Facebook microposts via a mash-up API and tracking its data provenance. In Ajith Abraham, E. Corchado, S.-Y. Han, W. Guo, J. Corchado, & A. Vasilakos (Eds.), 2011 7th International Conference on Next Generation Web Services Practices (pp. 342–345). Presented at the 7th International conference on Next Generation Web Services Practices, Piscataway, NJ, USA: IEEE.
Vancouver
1.
Steiner T, Verborgh R, Vallés JG, Van de Walle R. Adding meaning to Facebook microposts via a mash-up API and tracking its data provenance. In: Abraham A, Corchado E, Han S-Y, Guo W, Corchado J, Vasilakos A, editors. 2011 7th International Conference on Next Generation Web Services Practices. Piscataway, NJ, USA: IEEE; 2011. p. 342–5.
MLA
Steiner, Thomas, Ruben Verborgh, Joaquim Gabarró Vallés, et al. “Adding Meaning to Facebook Microposts via a Mash-up API and Tracking Its Data Provenance.” 2011 7th International Conference on Next Generation Web Services Practices. Ed. Ajith Abraham et al. Piscataway, NJ, USA: IEEE, 2011. 342–345. Print.
@inproceedings{2003163,
  abstract     = {The social networking website Facebook offers to its users a feature called ldquostatus updatesrdquo (or just ldquostatusrdquo), which allows users to create microposts directed to all their contacts, or a subset thereof. Readers can respond to microposts, or in addition to that also click a ldquoLikerdquo button to show their appreciation for a certain micropost. Adding semantic meaning in the sense of unambiguous intended ideas to such microposts can, for example, be achieved via Natural Language Processing (NLP). Therefore, we have implemented a RESTful mash-up NLP API, which is based on a combination of several third party NLP APIs in order to retrieve more accurate results in the sense of emergence. In consequence, our API uses third party APIs opaquely in the background in order to deliver its output. In this paper, we describe how one can keep track of provenance, and credit back the contributions of each single API to the combined result of all APIs. In addition to that, we show how the existence of provenance metadata can help understand the way a combined result is formed, and optimize the result combination process. Therefore, we use the HTTP Vocabulary in RDF and the Provenance Vocabulary. The main contribution of our work is a description of how provenance metadata can be automatically added to the output of mash-up APIs like the one presented here.},
  author       = {Steiner, Thomas and Verborgh, Ruben and Vall{\'e}s, Joaquim Gabarr{\'o} and Van de Walle, Rik},
  booktitle    = {2011 7th International Conference on Next Generation Web Services Practices},
  editor       = {Abraham, Ajith and Corchado, Emilio and Han, Sang-Yong and Guo, Weisen and Corchado, Juan and Vasilakos, Athanasios},
  isbn         = {9781457711275},
  keyword      = {meta data,application program interfaces,natural language processing,social networking (online),vocabulary},
  language     = {eng},
  location     = {Salamanca, Spain},
  pages        = {342--345},
  publisher    = {IEEE},
  title        = {Adding meaning to Facebook microposts via a mash-up API and tracking its data provenance},
  url          = {http://dx.doi.org/10.1109/NWeSP.2011.6088202},
  year         = {2011},
}

Altmetric
View in Altmetric
Web of Science
Times cited: