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Found 9 papers, 2 papers with code
Using Full-Text Content to Characterize and Identify Best Seller Books
Such an outcome suggests that it is unfeasible to predict the success of books with high accuracy using only the full content of the texts.
Recovering network topology and dynamics via sequence characterization
Given that in many real scenarios, the underlying processes generating the sequence is hidden, we investigate whether the reconstruction of the network via the co-occurrence method is useful to recover both the network topology and agent dynamics generating sequences.
Text characterization based on recurrence networks
In particular, texts are also characterized by a hierarchical structure that can be approached by using multi-scale concepts and methods.
Robustness modularity in complex networks
Here we propose a new measure based on the concept of robustness: modularity is the probability to find trivial partitions when the structure of the network is randomly perturbed.
A pattern recognition approach for distinguishing between prose and poetry
Interestingly, by using an approach based on complex networks to visualize the similarities between the different texts considered, we found that the patterns of poetry vary much more than prose.
Malleability of complex networks
In this work, we suggest the concept of malleability of a network, which is defined as the exponential of the entropy of the probabilities of each possible unfolding with respect to a given configuration.
Physics and Society Social and Information Networks
Representation of texts as complex networks: a mesoscopic approach
In order to grasp the mesoscopic characteristics of semantical content in written texts, we devised a network model which is able to analyze documents in a multi-scale fashion.
Complex systems: features, similarity and connectivity
More specifically, the identification of the main areas to which the concepts frequently used in complex networks can be applied paves the way to adopting and applying a larger set of concepts and methods deriving from those respective areas.
Concentric network symmetry grasps authors' styles in word adjacency networks
A statistical analysis of the symmetry distribution performed in several novels showed that most of the words do not display symmetric patterns of connectivity.
