Trading Cultural Goods in the Era of Digital Piracy

The issue of digital piracy as violation of intellectual property rights is a hot button among many governments around the world. Until now, nor legislation or its enforcement have managed to keep up with the most recent technologies facilitating piracy. Piracy rates may significantly affect both internal demand and international trade of cultural goods. This paper aims to empirically assess the effect of digital piracy on bilateral trade in cultural goods. We focus on trade in music and media. Analysing an 11-year panel of 25 countries, we find that piracy does affect negatively bilateral trade, although to a varying extent.trade; cultural goods; piracy; spatial filtering; network autocorrelation

Multitask Learning for Network Traffic Classification

Traffic classification has various applications in today's Internet, from resource allocation, billing and QoS purposes in ISPs to firewall and malware detection in clients. Classical machine learning algorithms and deep learning models have been widely used to solve the traffic classification task. However, training such models requires a large amount of labeled data. Labeling data is often the most difficult and time-consuming process in building a classifier. To solve this challenge, we reformulate the traffic classification into a multi-task learning framework where bandwidth requirement and duration of a flow are predicted along with the traffic class. The motivation of this approach is twofold: First, bandwidth requirement and duration are useful in many applications, including routing, resource allocation, and QoS provisioning. Second, these two values can be obtained from each flow easily without the need for human labeling or capturing flows in a controlled and isolated environment. We show that with a large amount of easily obtainable data samples for bandwidth and duration prediction tasks, and only a few data samples for the traffic classification task, one can achieve high accuracy. We conduct two experiment with ISCX and QUIC public datasets and show the efficacy of our approach

Trading Cultural Goods in the Era of Digital Piracy

The issue of digital piracy is a hot button among governments around the world. Piracy rates may significantly affect both internal and international trade of cultural goods. This paper aims to empirically assess the effect of digital piracy on bilateral trade in cultural goods. We focus on trade in music, films and media. Analysing an 11-year panel of 25 countries, we find that piracy does affect bilateral trade, but to varying extents.trade; trade; cultural goods; piracy; spatial filtering; network autocorrelation

Interest communities and flow roles in directed networks: the Twitter network of the UK riots

Directionality is a crucial ingredient in many complex networks in which information, energy or influence are transmitted. In such directed networks, analysing flows (and not only the strength of connections) is crucial to reveal important features of the network that might go undetected if the orientation of connections is ignored. We showcase here a flow-based approach for community detection in networks through the study of the network of the most influential Twitter users during the 2011 riots in England. Firstly, we use directed Markov Stability to extract descriptions of the network at different levels of coarseness in terms of interest communities, i.e., groups of nodes within which flows of information are contained and reinforced. Such interest communities reveal user groupings according to location, profession, employer, and topic. The study of flows also allows us to generate an interest distance, which affords a personalised view of the attention in the network as viewed from the vantage point of any given user. Secondly, we analyse the profiles of incoming and outgoing long-range flows with a combined approach of role-based similarity and the novel relaxed minimum spanning tree algorithm to reveal that the users in the network can be classified into five roles. These flow roles go beyond the standard leader/follower dichotomy and differ from classifications based on regular/structural equivalence. We then show that the interest communities fall into distinct informational organigrams characterised by a different mix of user roles reflecting the quality of dialogue within them. Our generic framework can be used to provide insight into how flows are generated, distributed, preserved and consumed in directed networks.Comment: 32 pages, 14 figures. Supplementary Spreadsheet available from: http://www2.imperial.ac.uk/~mbegueri/Docs/riotsCommunities.zip or http://rsif.royalsocietypublishing.org/content/11/101/20140940/suppl/DC

Identifying Key Sectors in the Regional Economy: A Network Analysis Approach Using Input-Output Data

By applying network analysis techniques to large input-output system, we identify key sectors in the local/regional economy. We overcome the limitations of traditional measures of centrality by using random-walk based measures, as an extension of Blochl et al. (2011). These are more appropriate to analyze very dense networks, i.e. those in which most nodes are connected to all other nodes. These measures also allow for the presence of recursive ties (loops), since these are common in economic systems (depending to the level of aggregation, most firms buy from and sell to other firms in the same industrial sector). The centrality measures we present are well suited for capturing sectoral effects missing from the usual output and employment multipliers. We also develop an R package (xtranat) for the processing of data from IMPLAN(R) models and for computing the newly developed measures

World city network research at a theoretical impasse::On the need to re-establish qualitative approaches to understanding agency in world city networks

From the late 1990s, the establishment of a new relational ‘turn’ in the study of world city connectedness in globalization has run parallel to the wider relational turn occurring in economic geography. Early work, built firmly upon a qualitative approach to the collection and analyses of new inter-city datasets, considered cities as being constituted by their relations with other cities. Subsequent research, however, would take a strong quantitative turn, best demonstrated through the articulation of the inter-locking world city network (ILWCN) ‘model’ for measuring relations between cities. In this paper, we develop a critique of research based around the ILWCN model, arguing that this ‘top down’ quantitative approach has now reached a theoretical impasse. To address this impasse, we argue for a move away from Structural approaches in which the firm is the main unit of analysis, towards qualitative approaches in which individual agency and practice are afforded greater importance

The Research Space: using the career paths of scholars to predict the evolution of the research output of individuals, institutions, and nations

In recent years scholars have built maps of science by connecting the academic fields that cite each other, are cited together, or that cite a similar literature. But since scholars cannot always publish in the fields they cite, or that cite them, these science maps are only rough proxies for the potential of a scholar, organization, or country, to enter a new academic field. Here we use a large dataset of scholarly publications disambiguated at the individual level to create a map of science-or research space-where links connect pairs of fields based on the probability that an individual has published in both of them. We find that the research space is a significantly more accurate predictor of the fields that individuals and organizations will enter in the future than citation based science maps. At the country level, however, the research space and citations based science maps are equally accurate. These findings show that data on career trajectories-the set of fields that individuals have previously published in-provide more accurate predictors of future research output for more focalized units-such as individuals or organizations-than citation based science maps