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Article

A. Hossein Farajpahlou

Success and effectiveness in automated library systems are two related issues that all users are normally looking for when buying or designing a new system. On the basis…

Abstract

Success and effectiveness in automated library systems are two related issues that all users are normally looking for when buying or designing a new system. On the basis of the available literature and opinions of automated library systems experts, 26 factors were identified as criteria for the success of automated library systems. Attitudes to these criteria of Australian university librarians and systems managers were examined in a survey conducted in 1993; 23 of these criteria were approved by the survey sample, and the other three were rejected. These criteria should be tested with other groups of experts in library automation to gain more generalisation on the findings.

Details

Library Review, vol. 48 no. 4
Type: Research Article
ISSN: 0024-2535

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Article

Peter Buell Hirsch

The purpose of this paper is to stimulate an urgent dialogue about the impact of automated opinion engines (“bots”) on the functioning of public institutions in democratic…

Abstract

Purpose

The purpose of this paper is to stimulate an urgent dialogue about the impact of automated opinion engines (“bots”) on the functioning of public institutions in democratic societies. While the use of political bots may or may not have influenced the recent US presidential election or the UK “Brexit” referendum, it is believed that the implications of the use of political bots are more broadly troubling. There is an urgent need for common standards to prevent the abuse of these powerful digital tools.

Design/methodology/approach

The paper is based on a review of recent pieces describing political bots and attempts to extrapolate our learnings from recent political campaigns to the broader context of the discussion of all public issues.

Findings

It was found that the use of political bots has a powerful ability to manipulate public opinion and could easily infect the totality of public discourse.

Research limitations/implications

The core data on which the author’s discussion is based are limited to primary research by a small number of data scientists. This pool needs to be significantly expanded.

Practical implications

The insights the author proposes should serve to stimulate an organized effort to develop common standards for the use of and to prevent the abuse of these automated opinion tools.

Social implications

Unless an effort along these lines is made, distrust in all democratic and transparent institutions is highly likely to decrease.

Originality/value

While much has been written about bots in politics, the author believes that this is the first attempt to trace the dangers of bots across a much broader set of community institutions.

Details

Journal of Business Strategy, vol. 38 no. 3
Type: Research Article
ISSN: 0275-6668

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Article

Deanna Osman, John Yearwood and Peter Vamplew

The purpose of this paper is to examine the usefulness of fusion as a means of improving the precision of automated opinion detection.

Abstract

Purpose

The purpose of this paper is to examine the usefulness of fusion as a means of improving the precision of automated opinion detection.

Design/methodology/approach

Five system fusion methods are proposed and tested using runs submitted by the Text REtrieval Conference (TREC) Blog06 participants as input. The methods include a voting method, an inverse rank method (IRM), a linear‐normalised score method and two weighted methods that use a weighted IRM score to rank the document.

Findings

Mean average precision (MAP) is used as an indicator of the performance of the runs in this study. The best system fusion method achieves a 55.5 percent higher MAP result compared with the highest MAP result of any individual run submitted by the Blog06 participants. This equates to an increase in detection of 2,398 relevant opinion documents (21 percent).

Practical implications

System fusion can be used to improve upon the results achieved by existing individual opinion detection systems. On the other hand, multiple opinion detection approaches can be combined into one system and fusion used to combine the results to build in diversity. Diversity within fusion inputs can increase the improvements achieved by fusion methods. The improved output from a diverse opinion detection system will then contain a higher number of relevant documents and reduce the incidence of high‐ranking non‐relevant documents and low‐ranking relevant documents.

Originality/value

The fusion methods proposed in this study demonstrate that simple fusion of opinion detection systems can improve performance.

Details

Online Information Review, vol. 33 no. 5
Type: Research Article
ISSN: 1468-4527

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Article

Georgios Kalamatianos, Symeon Symeonidis, Dimitrios Mallis and Avi Arampatzis

The rapid growth of social media has rendered opinion and sentiment mining an important area of research with a wide range of applications. This paper aims to focus on the…

Abstract

Purpose

The rapid growth of social media has rendered opinion and sentiment mining an important area of research with a wide range of applications. This paper aims to focus on the Greek language and the microblogging platform Twitter, investigating methods for extracting emotion of individual tweets as well as population emotion for different subjects (hashtags).

Design/methodology/approach

The authors propose and investigate the use of emotion lexicon-based methods as a mean of extracting emotion/sentiment information from social media. The authors compare several approaches for measuring the intensity of six emotions: anger, disgust, fear, happiness, sadness and surprise. To evaluate the effectiveness of the methods, the authors develop a benchmark dataset of tweets, manually rated by two humans.

Findings

Development of a new sentiment lexicon for use in Web applications. The authors then assess the performance of the methods with the new lexicon and find improved results.

Research limitations/implications

Automated emotion results of research seem promising and correlate to real user emotion. At this point, the authors make some interesting observations about the lexicon-based approach which lead to the need for a new, better, emotion lexicon.

Practical implications

The authors examine the variation of emotion intensity over time for selected hashtags and associate it with real-world events.

Originality/value

The originality in this research is the development of a training set of tweets, manually annotated by two independent raters. The authors “transfer” the sentiment information of these annotated tweets, in a meaningful way, to the set of words that appear in them.

Details

Journal of Systems and Information Technology, vol. 20 no. 2
Type: Research Article
ISSN: 1328-7265

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Book part

Debbie Hopkins and Tim Schwanen

Automated vehicle technologies dominate many visions of future systems of smart mobility. This chapter uses the approach of Transition Management to explore the…

Abstract

Automated vehicle technologies dominate many visions of future systems of smart mobility. This chapter uses the approach of Transition Management to explore the multi-actor governance processes around automated vehicle technologies in the United Kingdom (UK), with specific attention being paid to the role of the UK government. It shows the relatively comprehensive approach to automated vehicle innovation that has been adopted by the UK government, emerging across multiple domains including the creation of positive discourses around automation, and the facilitation of network building and demonstration projects. Framed by the Transition Management cycle of strategic, tactical, operational and reflexive activities, the chapter argues for greater integration across the levels of the cycle, and experimentation that moves beyond technological capability, to include the heterogeneous publics, in a more diverse set of roles than the current framing of ‘potential technology adopter’. The chapter points to the techno-optimism displayed by governments participating in the international race to vehicle automation, often with dual roles as both producers and consumers, and suggest that greater inclusivity, democracy, diversity and openness in the innovation process may contribute to context sensitive implementation.

Details

Governance of the Smart Mobility Transition
Type: Book
ISBN: 978-1-78754-317-1

Keywords

Content available

Abstract

Details

Autonomous Driving
Type: Book
ISBN: 978-1-78714-834-5

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Article

Clare M. Connor

Provides an overview of the implications of automation for stafftraining in libraries. Discusses the reported effects of automation onlibrary personnel, and explains the…

Abstract

Provides an overview of the implications of automation for staff training in libraries. Discusses the reported effects of automation on library personnel, and explains the significance of these for the planning of training. Considers the roles of the training organizer and the trainer. Outlines elements of the training programme, including timing, location, resources, methods, costs, evaluation, staff appraisal, and the need for continuity. Finally, raises considerations for suitable management style.

Details

Library Management, vol. 13 no. 6
Type: Research Article
ISSN: 0143-5124

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Article

Nigel L. Williams, Nicole Ferdinand and John Bustard

Advances in artificial intelligence (AI) natural language processing may see the emergence of algorithmic word of mouth (aWOM), content created and shared by automated

Abstract

Purpose

Advances in artificial intelligence (AI) natural language processing may see the emergence of algorithmic word of mouth (aWOM), content created and shared by automated tools. As AI tools improve, aWOM will increase in volume and sophistication, displacing eWOM as an influence on customer decision-making. The purpose of this paper is to provide an overview of the socio technological trends that have encouraged the evolution of informal infulence strategies from WOM to aWOM.

Design/methodology/approach

This paper examines the origins and path of development of influential customer communications from word of mouth (WOM) to electronic word of mouth (eWOM) and the emerging trend of aWOM. The growth of aWOM is theorized as a result of new developments in AI natural language processing tools along with autonomous distribution systems in the form of software robots and virtual assistants.

Findings

aWOM may become a dominant source of information for tourists, as it can support multimodal delivery of useful contextual information. Individuals, organizations and social media platforms will have to ensure that aWOM is developed and deployed responsibly and ethically.

Practical implications

aWOM may emerge as the dominant source of information for tourist decision-making, displacing WOM or eWOM. aWOM may also impact online opinion leaders, as they may be challenged by algorithmically generated content. aWOM tools may also generate content using sensors on personal devices, creating privacy and information security concerns if users did not give permission for such activities.

Originality/value

This paper is the first to theorize the emergence of aWOM as autonomous AI communication within the framework of unpaid influence or WOM. As customer engagement will increasingly occur in algorithmic environments that comprise person–machine interactions, aWOM will influence future tourism research and practice.

Details

Tourism Review, vol. 75 no. 1
Type: Research Article
ISSN: 1660-5373

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Article

Atika Qazi, Ram Gopal Raj, Glenn Hardaker and Craig Standing

The purpose of this paper is to map the evidence provided on the review types, and explain the challenges faced by classification techniques in sentiment analysis (SA)…

Abstract

Purpose

The purpose of this paper is to map the evidence provided on the review types, and explain the challenges faced by classification techniques in sentiment analysis (SA). The aim is to understand how traditional classification technique issues can be addressed through the adoption of improved methods.

Design/methodology/approach

A systematic review of literature was used to search published articles between 2002 and 2014 and identified 24 papers that discuss regular, comparative, and suggestive reviews and the related SA techniques. The authors formulated and applied specific inclusion and exclusion criteria in two distinct rounds to determine the most relevant studies for the research goal.

Findings

The review identified nine practices of review types, eight standard machine learning classification techniques and seven practices of concept learning Sentic computing techniques. This paper offers insights on promising concept-based approaches to SA, which leverage commonsense knowledge and linguistics for tasks such as polarity detection. The practical implications are also explained in this review.

Research limitations/implications

The findings provide information for researchers and traders to consider in relation to a variety of techniques for SA such as Sentic computing and multiple opinion types such as suggestive opinions.

Originality/value

Previous literature review studies in the field of SA have used simple literature review to find the tasks and challenges in the field. In this study, a systematic literature review is conducted to find the more specific answers to the proposed research questions. This type of study has not been conducted in the field previously and so provides a novel contribution. Systematic reviews help to reduce implicit researcher bias. Through adoption of broad search strategies, predefined search strings and uniform inclusion and exclusion criteria, systematic reviews effectively force researchers to search for studies beyond their own subject areas and networks.

Details

Internet Research, vol. 27 no. 3
Type: Research Article
ISSN: 1066-2243

Keywords

Abstract

Details

Threats from Car Traffic to the Quality of Urban Life
Type: Book
ISBN: 978-0-08-048144-9

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