Mark-David McLaughlin

Visualization of Very Large Networks: The Co-starring Social Network

This chapter describes and contrasts two main approaches to visualizing the very large actor co-starring network. Technical details on how to construct the visualizations are provided and memory problems discussed. The chapter demonstrates a successful use of k-core techniques for visualizing large networks.

Movie analytics: Visualization of the co-starring network

This poster contributes a novel application of social network visualization techniques to the motion picture industry. We make the case and illustrate with examples that a visualization approach based on k-cores helps alleviate otherwise inextricable memory issues in analyses of the IMDb co-starring network, which contains more than 2.6 million actors displaying over a billion links, with degrees which can rise to about 50,000 and above for the most connected actors.

Movie Analytics and the Future of Film Finance. Are Oscars and Box Office Revenue Predictable

This chapter discusses to which extent modern analytics techniques can help us understand the success of movies, as measured by their box office or attributed Oscars. Interesting lessons emerge from our analyses. Predicting box office revenue on the basis of data available before the release of the movie remains difficult, even with state-of-the-art techniques. Prediction markets are a remarkably powerful tool at predicting success at Oscars. A moderate amount of controversy, as measured by the number of underlying themes raised by movie reviewers, may prove to be helpful in obtaining an Academy Award for Best Picture .

Capabilities and Skill Configurations of Information Security Incident Responders

This paper identifies skill sets that contribute to effective InfoSec incident response. Even though many organizations have staff dedicated to InfoSec incident response teams, there is a lack of consensus as to the skill set each team member needs to effectively perform his/her job, and general and specialized skills that need to be represented in incident response teams (but usually not all held by each team member). Previous guidance was offered based on non-empirical methods. In this study, we used the Repertory Grid (RepGrid) method to elicit lists of incident response skills from industry experts. Skill archetypes were then identified by clustering incident responders who share similar characteristics. The findings extend the Theory of Resource Complements and provide managers with practical guidance regarding the skill sets most critical to the incident response role.

InfoSec Research in Prominent IS Journals: Findings and Implications for the CIO and Board of Directors

Having reviewed 91 information security (InfoSec) studies published in top IS journals for a ten-year period (2004-2014), we discuss technical, behavioral, financial, and managerial challenges for CIOs and boards of directors, and offer suggestions for future practice-relevant research on preventing, preparing for, detecting and responding to InfoSec incidents.

What Do We Know About Analyzing Movie Data

This chapter gives a road map of the topics discussed in the monograph and briefly introduces what is meant by “Movie Analytics”.

Movie Attendance and Trends

This chapter demonstrates how to analyze longitudinal data on weekly attendance during several years in eight different movie theaters in France, all located in small to medium sized cities in the South West part of France (the movie theaters considered in this study have from 1 to 4 rooms). Necessary R code is included and discussed.

Can We Predict Oscars from Twitter and Movie Review Data

In this chapter, we focus the attention on whether text reviews of movies which are nominated for a Best Picture award carry any sign of the likelihood of a movie winning the award. We suggest that a measure of how controversial the movie is perceived to be, the value of which could be extracted by a text analysis of the reviews, is a potential predictor of a win, aside from other predictors identified in past work. This also is an opportunity to discuss text mining and sentiment analysis techniques.

Oscar Prediction and Prediction Markets

In this chapter we examine the role of prediction markets in evaluating the probability of a nominated motion picture receiving an Academy award. We illustrate the issue with the best picture award in 2013.

A high performance computing cluster under attack: the Titan incident

At the University of Oslo (UiO), CERT manager Margrete Raaum learned of a network attack on Titan, a high-performance computing cluster that supported research conducted by scientists at CERT and other research institutions across Europe. The case describes the incident response, investigation, and clarification of the information security events that took place. As soon as Raaum learned of the attack, she ordered that the system be disconnected from the Internet to contain the damage. Next, she launched an investigation, which over a few days pieced together logs from previous weeks to identify suspicious activity and locate the attack vector. Raaum hopes to soon return Titan to its prior safe condition. In order to do so, she must decide what tasks still need to be completed to validate the systems and determine if it is safe to reconnect it to the Internet. She must also consider further steps to improve her team’s ability to prevent, detect, and respond to similar incidents in the future. This case is designed for an undergraduate or graduate information security (infosec) class that includes students with varied technical and business backgrounds. The case supports discussion of technical and managerial infosec issues in inter-organizational systems – a topic that is currently underrepresented in major case collections.