Abstract
In a recent work some of the authors have developed an argumentative approach for discovering relevant opinions in Twitter discussions with probabilistic valued relationships. Given a Twitter discussion, the system builds an argument graph where each node denotes a tweet and each edge denotes a criticism relationship between a pair of tweets of the discussion. Relationships between tweets are associated with a probability value, indicating the uncertainty on whether they actually hold. In this work we introduce and investigate a natural extension of the representation model, referred as probabilistic author-centered model. In this model, tweets by a same author are grouped, describing his/her opinion in the discussion, and are represented with a single node in the graph, while edges stand for criticism relationships between author’s opinions. In this new model, interactions between authors can give rise to circular criticism relationships, and the probability of one opinion criticizing another is evaluated from the criticism probabilities among the individual tweets in both opinions.
This work was partially funded by the Spanish MINECO/FEDER Projects TIN2015-71799-C2-1-P and TIN2015-71799-C2-2-P, by the European H2020 Grant Agreement 723596, and by the 2017 SGR 1537 and 172.
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Notes
- 1.
The discussion URL is https://twitter.com/jordievole/status/574324656905281538.
- 2.
This is because in our probabilistic model the label \(P(t_1,t_2)\) assigned to an edge \((t_1,t_2)\) is based only on the information inside the tweets \(t_1\) and \(t_2\) and not on other answers from the same authors.
- 3.
We plan to implement the other weighting schemes in the near future.
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Alsinet, T., Argelich, J., Béjar, R., Esteva, F., Godo, L. (2018). A Probabilistic Author-Centered Model for Twitter Discussions. In: Medina, J., et al. Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations. IPMU 2018. Communications in Computer and Information Science, vol 854. Springer, Cham. https://doi.org/10.1007/978-3-319-91476-3_56
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