Generation and Analysis of a Social Network: Hamlet

This paper examines the generation and analysis of a social network produced from Shakespeare’s play Hamlet. An XML file of Hamlet was parsed to extract the characters within the play and also identify when the characters appeared within the same scene. After parsing the speakers and the connections between characters, a network graph was generated that displayed all the characters in Hamlet, represented by nodes, and edges that represented the connections between characters as measured by their scene co-appearance. The results of the network graph were then compared to a published social network for Hamlet created by hand. The two social networks showed strong similarities in character centrality but also showed differences in the number of character nodes and edges. In addition to the case study, we present a suite of tools that provide a framework for computational analysis of future plays

Improving Reachability and Navigability in Recommender Systems

In this paper, we investigate recommender systems from a network perspective and investigate recommendation networks, where nodes are items (e.g., movies) and edges are constructed from top-N recommendations (e.g., related movies). In particular, we focus on evaluating the reachability and navigability of recommendation networks and investigate the following questions: (i) How well do recommendation networks support navigation and exploratory search? (ii) What is the influence of parameters, in particular different recommendation algorithms and the number of recommendations shown, on reachability and navigability? and (iii) How can reachability and navigability be improved in these networks? We tackle these questions by first evaluating the reachability of recommendation networks by investigating their structural properties. Second, we evaluate navigability by simulating three different models of information seeking scenarios. We find that with standard algorithms, recommender systems are not well suited to navigation and exploration and propose methods to modify recommendations to improve this. Our work extends from one-click-based evaluations of recommender systems towards multi-click analysis (i.e., sequences of dependent clicks) and presents a general, comprehensive approach to evaluating navigability of arbitrary recommendation networks

Spartan Daily March 8, 2010

Volume 134, Issue 20https://scholarworks.sjsu.edu/spartandaily/1236/thumbnail.jp

Temporal Network Analysis of Literary Texts

We study temporal networks of characters in literature focusing on "Alice's Adventures in Wonderland" (1865) by Lewis Carroll and the anonymous "La Chanson de Roland" (around 1100). The former, one of the most influential pieces of nonsense literature ever written, describes the adventures of Alice in a fantasy world with logic plays interspersed along the narrative. The latter, a song of heroic deeds, depicts the Battle of Roncevaux in 778 A.D. during Charlemagne's campaign on the Iberian Peninsula. We apply methods recently developed by Taylor and coworkers \cite{Taylor+2015} to find time-averaged eigenvector centralities, Freeman indices and vitalities of characters. We show that temporal networks are more appropriate than static ones for studying stories, as they capture features that the time-independent approaches fail to yield.Comment: 17 pages, 11 figure

Complex network analysis of literary and scientific texts

We present results from our quantitative study of statistical and network properties of literary and scientific texts written in two languages: English and Polish. We show that Polish texts are described by the Zipf law with the scaling exponent smaller than the one for the English language. We also show that the scientific texts are typically characterized by the rank-frequency plots with relatively short range of power-law behavior as compared to the literary texts. We then transform the texts into their word-adjacency network representations and find another difference between the languages. For the majority of the literary texts in both languages, the corresponding networks revealed the scale-free structure, while this was not always the case for the scientific texts. However, all the network representations of texts were hierarchical. We do not observe any qualitative and quantitative difference between the languages. However, if we look at other network statistics like the clustering coefficient and the average shortest path length, the English texts occur to possess more clustered structure than do the Polish ones. This result was attributed to differences in grammar of both languages, which was also indicated in the Zipf plots. All the texts, however, show network structure that differs from any of the Watts-Strogatz, the Barabasi-Albert, and the Erdos-Renyi architectures

Kronika

Report from the Alice Through the Ages conference held in Cambridge, UK in September 2015. Report from the Alice 150 conference held in New York, USA in October 2015.Izvještaj s konferencije "Alice Through the Ages: Revisiting a Classic at 150" održane u Cambridgeu Velikoj Britaniji u rujnu 2015. godine. Izvještaj s konferencije "Alice 150" održane u New Yorku, Sjedinjenim Američkim državama u listopadu 2015. godine

Extraction and Analysis of Dynamic Conversational Networks from TV Series

Identifying and characterizing the dynamics of modern tv series subplots is an open problem. One way is to study the underlying social network of interactions between the characters. Standard dynamic network extraction methods rely on temporal integration, either over the whole considered period, or as a sequence of several time-slices. However, they turn out to be inappropriate in the case of tv series, because the scenes shown onscreen alternatively focus on parallel storylines, and do not necessarily respect a traditional chronology. In this article, we introduce Narrative Smoothing, a novel network extraction method taking advantage of the plot properties to solve some of their limitations. We apply our method to a corpus of 3 popular series, and compare it to both standard approaches. Narrative smoothing leads to more relevant observations when it comes to the characterization of the protagonists and their relationships, confirming its appropriateness to model the intertwined storylines constituting the plots.Comment: arXiv admin note: substantial text overlap with arXiv:1602.0781

Kronika

Report from the Alice Through the Ages conference held in Cambridge, UK in September 2015. Report from the Alice 150 conference held in New York, USA in October 2015.Izvještaj s konferencije "Alice Through the Ages: Revisiting a Classic at 150" održane u Cambridgeu Velikoj Britaniji u rujnu 2015. godine. Izvještaj s konferencije "Alice 150" održane u New Yorku, Sjedinjenim Američkim državama u listopadu 2015. godine