Research and Methodological Foundations of Transaction Log Analysis

Research and Methodological Foundations of Transaction Log Analysis

Bernard J. Jansen (Pennsylvania State University, USA), Isak Taksa (Baruch College, City University of New York, USA) and Amanda Spink (Queensland University of Technology, Australia)
Copyright: © 2009 |Pages: 16
DOI: 10.4018/978-1-59904-974-8.ch001
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Abstract

This chapter outlines and discusses theoretical and methodological foundations for transaction log analysis. We first address the fundamentals of transaction log analysis from a research viewpoint and the concept of transaction logs as a data collection technique from the perspective of behaviorism. From this research foundation, we move to the methodological aspects of transaction log analysis and examine the strengths and limitations of transaction logs as trace data. We then review the conceptualization of transaction log analysis as an unobtrusive approach to research, and present the power and deficiency of the unobtrusive methodological concept, including benefits and risks of transaction log analysis specifically from the perspective of an unobtrusive method. Some of the ethical questions concerning the collection of data via transaction log applications are discussed.
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Introduction

Conducting research involves the use of both a set of theoretical constructs and methods for investigation. For empirical research, the results are linked conceptually to the data collection process. Quality research papers must contain a thorough methodology section. In order to understand empirical research and the implications of the results, one must thoroughly understand the techniques by which the researcher collected and analyzed the data. When conducting research concerning users and information systems, there are a variety of methods at ones disposal. These research methods are qualitative, quantitative, or mixed. The selection of an appropriate method is critically important if the research is to have effective outcomes and be efficient in execution. The data collection also involves a choice of methods. Transaction logs and transaction log analysis is one approach to data collection and a research method for both system performance and user behavior analysis that has been used since 1967 (Meister & Sullivan, 1967) and in peer reviewed research since 1975 (Penniman, 1975).

A transaction log is an electronic record of interactions that have occurred between a system and users of that system. These log files can come from a variety of computers and systems (Websites, OPAC, user computers, blogs, listserv, online newspapers, etc.), basically any application that can record the user – system – information interactions. Transaction log analysis is the methodological approach to studying online systems and users of these systems. Peters (1993) defines transaction log analysis as the study of electronically recorded interactions between on-line information retrieval systems and the persons who search for information found in those systems. Since the advent of the Internet, we have to modify Peter’s (1993) definition, expanding it to include systems other than information retrieval systems.

Transaction log analysis is a broad categorization of methods that covers several sub-categorizations, including Web log analysis (i.e., analysis of Web system logs), blog analysis, and search log analysis (analysis of search engine logs). Transaction log analysis enables macro-analysis of aggregate user data and patterns and microanalysis of individual search patterns. The results from the analyzed data help develop improved systems and services based on user behavior or system performance.

From the user behavior side, transaction log analysis is one of a class of unobtrusive methods (a.k.a., non-reactive or low-constraint). Unobtrusive methods allow data collection without directly interfacing with participants. The research literature specifically describes unobtrusive approaches as those that do not require a response from participants (c.f., McGrath, 1994; Page, 2000; Webb, Campbell, Schwarz, & Sechrest, 2000). This data can be observational or existing data. Unobtrusive methods are in contrast to obtrusive or reactive approaches such as questionnaires, tests, laboratory studies, and surveys (Webb, Campbell, Schwartz, Sechrest, & Grove, 1981). A laboratory experiment is an example of an extreme obtrusive method. Certainly, the line between unobtrusive and obtrusive methods is sometimes blurred. For example, conducting a survey to gauge the reaction of users to information systems is an obtrusive method. However, using the posted results from the survey is an unobtrusive method.

In this chapter, we address the research and methodological foundations of transaction log analysis. We first address the concept of transaction logs as a data collection technique from the perspective of behaviorism. We then review the conceptualization of transaction log analysis as trace data and an unobtrusive method. We present the strengths and shortcomings of the unobtrusive approach, including benefits and shortcomings of transaction log analysis specifically from the perspective of an unobtrusive method. We end with a short summary and open questions of transaction logging as a data collection method.

The use of transaction logs for academic purposes certainly falls conceptually within the confines of the behaviorism paradigm of research. The behaviorism approach is the conceptual basis for the transaction log methodology.

Key Terms in this Chapter

Behaviorism: A research approach that emphasizes the outward behavioral aspects of thought. For transaction log analysis, we take a more open view of behaviorism. In this more encompassing view, behaviorism emphasizes the observed behaviors without discounting the inner aspects that may accompany these outward behaviors.

Transaction Log Analysis: A broad categorization of methods that covers several sub-categorizations, including Web log analysis (i.e., analysis of Web system logs), blog analysis and search log analysis (analysis of search engine logs).

Ethogram: An index of the behavioral patterns of a unit. An ethogram details the different forms of behavior that an actor displays. In most cases, it is desirable to create an ethogram in which the categories of behavior are objective, discrete, not overlapping with each other. The definitions of each behavior should be clear, detailed and distinguishable from each other. Ethograms can be as specific or general as the study or field warrants.

Transaction Log: An electronic record of interactions that have occurred between a system and users of that system. These log files can come from a variety of computers and systems (Websites, OPAC, user computers, blogs, listserv, online newspapers, etc.), basically any application that can record the user – system – information interactions. For transaction log analysis, behavior is the essential construct of the behaviorism paradigm. At its most basic, a behavior is an observable activity of a person, animal, team, organization, or system. Like many basic constructs, behavior is an overloaded term, as it also refers to the aggregate set of responses to both internal and external stimuli. Therefore, behaviors address a spectrum of actions. Because of the many associations with the term, it is difficult to characterize a term like behavior without specifying a context in which it takes place to provide meaning.

Unobtrusive Methods: Research practices that do not require the researcher to intrude in the context of the actors. Unobtrusive methods do not involve direct elicitation of data from the research participants or actors. This approach is in contrast to obtrusive methods such as laboratory experiments and surveys requiring that the researchers physically interject themselves into the environment being studied.

Trace Data (or measures): Offer a sharp contrast to directly collected data. The greatest strength of trace data is that it is unobtrusive. The collection of the data does not interfere with the natural flow of behavior and events in the given context. Since the data is not directly collected, there is no observer present in the situation where the behaviors occur to affect the participants’ actions. Trace data is unique; as unobtrusive and nonreactive data, it can make a very valuable research course of action. In the past, trace data was often time consuming to gather and process, making such data costly. With the advent of transaction logging software, trace data for the studying of behaviors of users and systems has really taken off.

Complete Chapter List

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Table of Contents
Preface
Bernard J. Jansen, Amanda Spink, Isak Taksa
Chapter 1
Bernard J. Jansen, Isak Taksa, Amanda Spink
This chapter outlines and discusses theoretical and methodological foundations for transaction log analysis. We first address the fundamentals of... Sample PDF
Research and Methodological Foundations of Transaction Log Analysis
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Chapter 2
W. David Penniman
This historical review of the birth and evolution of transaction log analysis applied to information retrieval systems provides two perspectives.... Sample PDF
Historic Perspective of Log Analysis
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Chapter 3
Lee Rainie, Bernard J. Jansen
Every research methodology for data collection has both strengths and limitations, and this is certainly true for transaction log analysis.... Sample PDF
Surveys as a Complementary Method for Web Log Analysis
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Chapter 4
Sam Ladner
This chapter aims to improve the rigor and legitimacy of Web-traffic measurement as a social research method. I compare two dominant forms of... Sample PDF
Watching the Web: An Ontological and Epistemological Critique of Web-Traffic Measurement
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Chapter 5
Kirstie Hawkey
This chapter examines two aspects of privacy concerns that must be considered when conducting studies that include the collection of Web logging... Sample PDF
Privacy Concerns for Web Logging Data
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Chapter 6
Bernard J. Jansen
Exploiting the data stored in search logs of Web search engines, Intranets, and Websites can provide important insights into understanding the... Sample PDF
The Methodology of Search Log Analysis
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Chapter 7
Anthony Ferrini, Jakki J. Mohr
As the Web’s popularity continues to grow and as new uses of the Web are developed, the importance of measuring the performance of a given Website... Sample PDF
Uses, Limitations, and Trends in Web Analytics
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Chapter 8
Danielle Booth
This chapter is an overview of the process of Web analytics for Websites. It outlines how visitor information such as number of visitors and visit... Sample PDF
A Review of Methodologies for Analyzing Websites
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Chapter 9
Gi Woong Yun
This chapter discusses validity of units of analysis of Web log data. First, Web log units are compared to the unit of analysis of television to... Sample PDF
The Unit of Analysis and the Validity of Web Log Data
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Chapter 10
Kirstie Hawkey, Melanie Kellar
This chapter presents recommendations for reporting context in studies of Web usage including Web browsing behavior. These recommendations consist... Sample PDF
Recommendations for Reporting Web Usage Studies
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Chapter 11
Seda Ozmutlu, Huseyin C. Ozmutlu, Amanda Spink
This chapter summarizes the progress of search engine user behavior analysis from search engine transaction log analysis to estimation of user... Sample PDF
From Analysis to Estimation of User Behavior
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Chapter 12
Gheorghe Muresan
In this chapter, we describe and discuss a methodological framework that integrates analysis of interaction logs with the conceptual design of the... Sample PDF
An Integrated Approach to Interaction Design and Log Analysis
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Chapter 13
Brian Detlor, Maureen Hupfer, Umar Ruhi
This chapter provides various tips for practitioners and researchers who wish to track end-user Web information seeking behavior. These tips are... Sample PDF
Tips for Tracking Web Information Seeking Behavior
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Chapter 14
Sandro José Rigo
Adaptive Hypermedia is an effective approach to automatic personalization that overcomes the difficulties and deficiencies of traditional Web... Sample PDF
Identifying Users Stereotypes for Dynamic Web Pages Customization
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Chapter 15
Brian K. Smith, Priya Sharma, Kyu Yon Lim, Goknur Kaplan Akilli, KyoungNa Kim, Toru Fujimoto
Computers and networking technologies have led to increases in the development and sustenance of online communities, and much research has focused... Sample PDF
Finding Meaning in Online, Very-Large Scale Conversations
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Chapter 16
Isak Taksa, Sarah Zelikovitz, Amanda Spink
Search query classification is a necessary step for a number of information retrieval tasks. This chapter presents an approach to non-hierarchical... Sample PDF
Machine Learning Approach to Search Query Classification
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Chapter 17
Seda Ozmutlu, Huseyin C. Ozmutlu, Amanda Spink
This chapter emphasizes topic analysis and identification of search engine user queries. Topic analysis and identification of queries is an... Sample PDF
Topic Analysis and Identification of Queries
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Chapter 18
Elmer V. Bernstam, Jorge R. Herskovic, William R. Hersh
Clinicians, researchers and members of the general public are increasingly using information technology to cope with the explosion in biomedical... Sample PDF
Query Log Analysis in Biomedicine
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Chapter 19
Michael Chau, Yan Lu, Xiao Fang, Christopher C. Yang
More non-English contents are now available on the World Wide Web and the number of non-English users on the Web is increasing. While it is... Sample PDF
Processing and Analysis of Search Query Logs in Chinese
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Chapter 20
Udo Kruschwitz, Nick Webb, Richard Sutcliffe
The theme of this chapter is the improvement of Information Retrieval and Question Answering systems by the analysis of query logs. Two case studies... Sample PDF
Query Log Analysis for Adaptive Dialogue-Driven Search
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Chapter 21
Mimi Zhang
In this chapter, we present the action-object pair approach as a conceptual framework for conducting transaction log analysis. We argue that there... Sample PDF
Using Action-Object Pairs as a Conceptual Framework for Transaction Log Analysis
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Chapter 22
Paul DiPerna
This chapter proposes a new theoretical construct for evaluating Websites that facilitate online social networks. The suggested model considers... Sample PDF
Analysis and Evaluation of the Connector Website
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Chapter 23
Marie-Francine Moens
This chapter introduces information extraction from blog texts. It argues that the classical techniques for information extraction that are commonly... Sample PDF
Information Extraction from Blogs
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Chapter 24
Adriana Andrade Braga
This chapter explores the possibilities and limitations of nethnography, an ethnographic approach applied to the study of online interactions... Sample PDF
Nethnography: A Naturalistic Approach Towards Online Interaction
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Chapter 25
Isak Taksa, Amanda Spink, Bernard J. Jansen
Web log analysis is an innovative and unique field constantly formed and changed by the convergence of various emerging Web technologies. Due to its... Sample PDF
Web Log Analysis: Diversity of Research Methodologies
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About the Contributors