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Analogical News Angles from Text Similarity

Conference paper
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Part of the Lecture Notes in Computer Science book series (LNCS, volume 11927)

Abstract

The paper presents an algorithm providing creativity support to journalists. It suggests analogical transfer of news angles from reports written about different events than the one the journalist is working on. The problem is formulated as a matching problem, where news reports with similar wordings from two events are matched, and unmatched reports from previous cases are selected as candidates for a news angle transfer. The approach is based on document similarity measures for matching and selection of transferable candidates. The algorithm has been tested on a small data set and show that the concept may be viable, but needs more exploration and evaluation in journalistic practice.

Keywords

Computational creativity Analogical reasoning Document similarity Journalism 

Notes

Acknowledgement

The News Angler project is funded by the Norwegian Research Council’s IKTPLUSS programme as project 275872.

References

  1. 1.
    Altheide, D.L., Rasmussen, P.K.: Becoming news: a study of two newsrooms. Sociol. Work. Occup. 3(2), 223–246 (1976)CrossRefGoogle Scholar
  2. 2.
    Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet allocation. J. Mach. Learn. Res. 3, 993–1022 (2003)zbMATHGoogle Scholar
  3. 3.
    Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: Bert: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)
  4. 4.
    Falkenhainer, B., Forbus, K.D., Gentner, D.: The structure-mapping engine: algorithm and examples. Artif. Intell. 41(1), 1–63 (1989)CrossRefGoogle Scholar
  5. 5.
    Gallofré Ocaña, M., Nyre, L., Opdahl, A.L., Tessem, B., Trattner, C., Veres, C.: Towards a big data platform for news angles. In: Proceedings of the 4th Norwegian Big Data Symposium (NOBIDS 2018), vol. 2316, pp. 17–29. CEUR Workshop Proceedings, November 2018Google Scholar
  6. 6.
    Gravanis, G., Vakali, A., Diamantaras, K., Karadais, P.: Behind the cues: a benchmarking study for fake news detection. Expert. Syst. Appl. 128, 201–213 (2019)CrossRefGoogle Scholar
  7. 7.
    Kusner, M., Sun, Y., Kolkin, N., Weinberger, K.: From word embeddings to document distances. In: Bach, F., Blei, D. (eds.) Proceedings of the 32nd International Conference on Machine Learning. Proceedings of Machine Learning Research, vol. 37, pp. 957–966. PMLR, Lille, France, 07–09 July 2015Google Scholar
  8. 8.
    Lewis, S.C., Westlund, O.: Big data and journalism: epistemology, expertise, economics, and ethics. Digit. J. 3(3), 447–466 (2015)Google Scholar
  9. 9.
    Manning, C.D., Raghavan, P., Schütze, H.: Introduction to Information Retrieval. Cambridge Univ. Press, New York (2008)CrossRefGoogle Scholar
  10. 10.
    Miroshnichenko, A.: AI to bypass creativity. Will robots replace journalists? (the answer is “yes”). Information 9(7), 183 (2018)CrossRefGoogle Scholar
  11. 11.
    Opdahl, A.L., Tessem, B.: Towards ontological support for journalistic angles. In: Reinhartz-Berger, I., Zdravkovic, J., Gulden, J., Schmidt, R. (eds.) BPMDS/EMMSAD -2019. LNBIP, vol. 352, pp. 279–294. Springer, Cham (2019).  https://doi.org/10.1007/978-3-030-20618-5_19CrossRefGoogle Scholar
  12. 12.
    Simonite, T.: Robot Writing Moves from Journalism to Wall Street (2015). https://www.technologyreview.com/s/533976/robot-journalist-finds-new-work-on-wall-street/
  13. 13.
    Speer, R., Chin, J., Havasi, C.: Conceptnet 5.5: an open multilingual graph of general knowledge. In: Proceedings of the 21st AAAI, San Francisco, USA, 4–9 February, pp. 4444–4451 (2017)Google Scholar
  14. 14.
    Yang, Z., Dai, Z., Yang, Y., Carbonell, J., Salakhutdinov, R., Le, Q.V.: XLNet: Generalized Autoregressive Pretraining for Language Understanding. arXiv:1906.08237 [cs], June 2019. http://arxiv.org/abs/1906.08237

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Information Science and Media StudiesUniversity of BergenBergenNorway

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