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Scott A. Hale

Bio: Scott A. Hale is an academic researcher from University of Oxford. The author has contributed to research in topics: Social media & Collective action. The author has an hindex of 23, co-authored 91 publications receiving 1792 citations. Previous affiliations of Scott A. Hale include The Turing Institute & Eckerd College.


Papers
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Journal ArticleDOI
TL;DR: This article compares three automated language identification packages to Twitter's user interface language setting and to a human coding of languages to identify common sources of disagreement and demonstrates that in many cases user-entered profile locations differ from the physical locations from which users are actually tweeting.
Abstract: The movements of ideas and content between locations and languages are unquestionably crucial concerns to researchers of the information age, and Twitter has emerged as a central, global platform on which hundreds of millions of people share knowledge and information. A variety of research has attempted to harvest locational and linguistic metadata from tweets to understand important questions related to the 300 million tweets that flow through the platform each day. Much of this work is carried out with only limited understandings of how best to work with the spatial and linguistic contexts in which the information was produced, however. Furthermore, standard, well-accepted practices have yet to emerge. As such, this article studies the reliability of key methods used to determine language and location of content in Twitter. It compares three automated language identification packages to Twitter's user interface language setting and to a human coding of languages to identify common sources of disagreemen...

310 citations

Book
24 Nov 2015
TL;DR: In this paper, the authors use experiments that test how social media influence citizens deciding whether or not to participate and identify which types of people are willing to participate at an early stage in a mobilization when there are few supporters or signals of viability.
Abstract: As people spend increasing proportions of their daily lives using social media, such as Twitter and Facebook, they are being invited to support myriad political causes by sharing, liking, endorsing, or downloading. Chain reactions caused by these tiny acts of participation form a growing part of collective action today, from neighborhood campaigns to global political movements. Political Turbulence reveals that, in fact, most attempts at collective action online do not succeed, but some give rise to huge mobilizationseven revolutions. Drawing on large-scale data generated from the Internet and real-world events, this book shows how mobilizations that succeed are unpredictable, unstable, and often unsustainable. To better understand this unruly new force in the political world, the authors use experiments that test how social media influence citizens deciding whether or not to participate. They show how different personality types react to social influences and identify which types of people are willing to participate at an early stage in a mobilization when there are few supporters or signals of viability. The authors argue that pluralism is the model of democracy that is emerging in the social media agenot the ordered, organized vision of early pluralists, but a chaotic, turbulent form of politics. This book demonstrates how data science and experimentation with social data can provide a methodological toolkit for understanding, shaping, and perhaps even predicting the outcomes of this democratic turbulence.

206 citations

Proceedings ArticleDOI
01 Aug 2019
TL;DR: In this article, the authors delineate and clarify the main challenges and frontiers in the abusive content detection field, critically evaluate their implications and discuss potential solutions, and highlight ways in which social scientific insights can advance research.
Abstract: Online abusive content detection is an inherently difficult task. It has received considerable attention from academia, particularly within the computational linguistics community, and performance appears to have improved as the field has matured. However, considerable challenges and unaddressed frontiers remain, spanning technical, social and ethical dimensions. These issues constrain the performance, efficiency and generalizability of abusive content detection systems. In this article we delineate and clarify the main challenges and frontiers in the field, critically evaluate their implications and discuss potential solutions. We also highlight ways in which social scientific insights can advance research. We discuss the lack of support given to researchers working with abusive content and provide guidelines for ethical research.

153 citations

Proceedings ArticleDOI
13 May 2019
TL;DR: This work creates a new multimodal deep neural architecture for joint classification of age, gender, and organization-status of social media users that operates in 32 languages and substantially outperforms current state of the art while also reducing algorithmic bias.
Abstract: Social media provide access to behavioural data at an unprecedented scale and granularity. However, using these data to understand phenomena in a broader population is difficult due to their non-representativeness and the bias of statistical inference tools towards dominant languages and groups. While demographic attribute inference could be used to mitigate such bias, current techniques are almost entirely monolingual and fail to work in a global environment. We address these challenges by combining multilingual demographic inference with post-stratification to create a more representative population sample. To learn demographic attributes, we create a new multimodal deep neural architecture for joint classification of age, gender, and organization-status of social media users that operates in 32 languages. This method substantially outperforms current state of the art while also reducing algorithmic bias. To correct for sampling biases, we propose fully interpretable multilevel regression methods that estimate inclusion probabilities from inferred joint population counts and ground-truth population counts. In a large experiment over multilingual heterogeneous European regions, we show that our demographic inference and bias correction together allow for more accurate estimates of populations and make a significant step towards representative social sensing in downstream applications with multilingual social media.

92 citations

Proceedings ArticleDOI
03 Nov 2019
TL;DR: A new evaluation framework for semantic change detection is proposed and it is found that using the whole time series is preferable over only comparing between the first and last time points; independently trained and aligned embeddings perform better than continuously trainedembeddings for long time periods; and that the reference point for comparison matters.
Abstract: Word embeddings are increasingly used for the automatic detection of semantic change; yet, a robust evaluation and systematic comparison of the choices involved has been lacking. We propose a new evaluation framework for semantic change detection and find that (i) using the whole time series is preferable over only comparing between the first and last time points; (ii) independently trained and aligned embeddings perform better than continuously trained embeddings for long time periods; and (iii) that the reference point for comparison matters. We also present an analysis of the changes detected on a large Twitter dataset spanning 5.5 years.

84 citations


Cited by
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Journal Article
TL;DR: This research examines the interaction between demand and socioeconomic attributes through Mixed Logit models and the state of art in the field of automatic transport systems in the CityMobil project.
Abstract: 2 1 The innovative transport systems and the CityMobil project 10 1.1 The research questions 10 2 The state of art in the field of automatic transport systems 12 2.1 Case studies and demand studies for innovative transport systems 12 3 The design and implementation of surveys 14 3.1 Definition of experimental design 14 3.2 Questionnaire design and delivery 16 3.3 First analyses on the collected sample 18 4 Calibration of Logit Multionomial demand models 21 4.1 Methodology 21 4.2 Calibration of the “full” model. 22 4.3 Calibration of the “final” model 24 4.4 The demand analysis through the final Multinomial Logit model 25 5 The analysis of interaction between the demand and socioeconomic attributes 31 5.1 Methodology 31 5.2 Application of Mixed Logit models to the demand 31 5.3 Analysis of the interactions between demand and socioeconomic attributes through Mixed Logit models 32 5.4 Mixed Logit model and interaction between age and the demand for the CTS 38 5.5 Demand analysis with Mixed Logit model 39 6 Final analyses and conclusions 45 6.1 Comparison between the results of the analyses 45 6.2 Conclusions 48 6.3 Answers to the research questions and future developments 52

4,784 citations

Book ChapterDOI
30 May 2018
TL;DR: Tata Africa Services (Nigeria) Limited as mentioned in this paper is a nodal point for Tata businesses in West Africa and operates as the hub of TATA operations in Nigeria and the rest of West Africa.
Abstract: Established in 2006, TATA Africa Services (Nigeria) Limited operates as the nodal point for Tata businesses in West Africa. TATA Africa Services (Nigeria) Limited has a strong presence in Nigeria with investments exceeding USD 10 million. The company was established in Lagos, Nigeria as a subsidiary of TATA Africa Holdings (SA) (Pty) Limited, South Africa and serves as the hub of Tata’s operations in Nigeria and the rest of West Africa.

3,658 citations

Journal Article
TL;DR: Thaler and Sunstein this paper described a general explanation of and advocacy for libertarian paternalism, a term coined by the authors in earlier publications, as a general approach to how leaders, systems, organizations, and governments can nudge people to do the things the nudgers want and need done for the betterment of the nudgees, or of society.
Abstract: NUDGE: IMPROVING DECISIONS ABOUT HEALTH, WEALTH, AND HAPPINESS by Richard H. Thaler and Cass R. Sunstein Penguin Books, 2009, 312 pp, ISBN 978-0-14-311526-7This book is best described formally as a general explanation of and advocacy for libertarian paternalism, a term coined by the authors in earlier publications. Informally, it is about how leaders, systems, organizations, and governments can nudge people to do the things the nudgers want and need done for the betterment of the nudgees, or of society. It is paternalism in the sense that "it is legitimate for choice architects to try to influence people's behavior in order to make their lives longer, healthier, and better", (p. 5) It is libertarian in that "people should be free to do what they like - and to opt out of undesirable arrangements if they want to do so", (p. 5) The built-in possibility of opting out or making a different choice preserves freedom of choice even though people's behavior has been influenced by the nature of the presentation of the information or by the structure of the decisionmaking system. I had never heard of libertarian paternalism before reading this book, and I now find it fascinating.Written for a general audience, this book contains mostly social and behavioral science theory and models, but there is considerable discussion of structure and process that has roots in mathematical and quantitative modeling. One of the main applications of this social system is economic choice in investing, selecting and purchasing products and services, systems of taxes, banking (mortgages, borrowing, savings), and retirement systems. Other quantitative social choice systems discussed include environmental effects, health care plans, gambling, and organ donations. Softer issues that are also subject to a nudge-based approach are marriage, education, eating, drinking, smoking, influence, spread of information, and politics. There is something in this book for everyone.The basis for this libertarian paternalism concept is in the social theory called "science of choice", the study of the design and implementation of influence systems on various kinds of people. The terms Econs and Humans, are used to refer to people with either considerable or little rational decision-making talent, respectively. The various libertarian paternalism concepts and systems presented are tested and compared in light of these two types of people. Two foundational issues that this book has in common with another book, Network of Echoes: Imitation, Innovation and Invisible Leaders, that was also reviewed for this issue of the Journal are that 1 ) there are two modes of thinking (or components of the brain) - an automatic (intuitive) process and a reflective (rational) process and 2) the need for conformity and the desire for imitation are powerful forces in human behavior. …

3,435 citations

Journal ArticleDOI
TL;DR: The Nature and Origins of Mass Opinion by John Zaller (1992) as discussed by the authors is a model of mass opinion formation that offers readers an introduction to the prevailing theory of opinion formation.
Abstract: Originally published in Contemporary Psychology: APA Review of Books, 1994, Vol 39(2), 225. Reviews the book, The Nature and Origins of Mass Opinion by John Zaller (1992). The author's commendable effort to specify a model of mass opinion formation offers readers an introduction to the prevailing vi

3,150 citations