***** To join INSNA, visit http://www.insna.org ***** Hello! I thought this might be of interest to you: http://mboudour.github.io/2015/10/28/Shakespeare's-Macbeth-Network.html Social networks commonly emerge out of a huge variety of data (physical, social, biological, medical, geographical, economical, political, psychological, cultural, artistic, technological, obtained from computers, social media, communication etc. etc.). The analysis and visualization of complex social networks aims at a better understanding of the underlying phenomena and processes wherever they come from. However, this is a very complicated task given that nowadays there is an easy access to large or complex data sets (usually referred to as "big data") for the analysis of which traditional (small-scale) processing applications are rather inadequate. Among other methodologies developed in order to confront such a challenge, machine learning techniques have been proven very efficient in facilitating the extraction of network structures from big data sets originating from a diverse range of sources. In particular, in the era of mass digitization of documents, books and all sorts of means of human communication, the repository of literature, literary texts, fiction, drama, theatrical plays, cinematographic films etc. provide a great opportunity for the exploration of any hidden network structure inside all these media. Thus in this article, as a typical example, we are going to consider William Shakespeare's Macbeth and show how elementary machine learning techniques (implemented through the Python programming language) might be used in order to detect actors, ties (here understood as conversational relationships) and attributes in the networks interwoven inside the plot of the play. Our goal is to visualize such networks at different levels (acts and scenes), assess the importance and centrality of the playing characters in them and examine how the attributes of characters interfere and mix with the network positions they hold and the network ties (relationships) they sustain (hence, evaluate the degree of homophily or assortativity of the considered networks). _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.insna.org). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.