scholarly journals Content analysis of 150 years of British periodicals

2017 ◽  
Vol 114 (4) ◽  
pp. E457-E465 ◽  
Author(s):  
Thomas Lansdall-Welfare ◽  
Saatviga Sudhahar ◽  
James Thompson ◽  
Justin Lewis ◽  
Nello Cristianini ◽  
...  
Keyword(s):  
Content Analysis ◽  
Cultural Change ◽  
Data Driven ◽  
Steady Increase ◽  
Named Entities ◽  
Fine Grained ◽  
Continuity And Change ◽  
Use Of Data ◽  
The United Kingdom ◽  
Regional Newspapers

Previous studies have shown that it is possible to detect macroscopic patterns of cultural change over periods of centuries by analyzing large textual time series, specifically digitized books. This method promises to empower scholars with a quantitative and data-driven tool to study culture and society, but its power has been limited by the use of data from books and simple analytics based essentially on word counts. This study addresses these problems by assembling a vast corpus of regional newspapers from the United Kingdom, incorporating very fine-grained geographical and temporal information that is not available for books. The corpus spans 150 years and is formed by millions of articles, representing 14% of all British regional outlets of the period. Simple content analysis of this corpus allowed us to detect specific events, like wars, epidemics, coronations, or conclaves, with high accuracy, whereas the use of more refined techniques from artificial intelligence enabled us to move beyond counting words by detecting references to named entities. These techniques allowed us to observe both a systematic underrepresentation and a steady increase of women in the news during the 20th century and the change of geographic focus for various concepts. We also estimate the dates when electricity overtook steam and trains overtook horses as a means of transportation, both around the year 1900, along with observing other cultural transitions. We believe that these data-driven approaches can complement the traditional method of close reading in detecting trends of continuity and change in historical corpora.

scholarly journals Flipped healthcare for better or worse

2019 ◽  
Vol 25 (3) ◽  
pp. 587-597 ◽  
Author(s):  
Helena Vallo Hult ◽  
Anders Hansson ◽  
Lars Svensson ◽  
Martin Gellerstedt
Keyword(s):  
Professional Practice ◽  
Cultural Change ◽  
Medical Profession ◽  
Rapid Development ◽  
Data Driven ◽  
Use Of Data ◽  
Resident Physicians ◽  
Clinical Scenarios ◽  
Online Sources

The medical profession is highly specialized, demanding continuous learning, while also undergoing rapid development in the rise of data-driven healthcare. Based on clinical scenarios, this study explores how resident physicians view their roles and practices in relation to informed patients and patient-centric digital technologies. The paper illustrates how the new role of patients alters physicians’ work and use of data to learn and update their professional practice. It suggests new possibilities for developing collegial competence and using patient experiences more systematically. Drawing on the notion of flipped healthcare, we argue that there is a need for new professional competencies in everyday data work, along with a change in attitudes, newly defined roles, and better ways to identify and develop reliable online sources. Finally, the role of patients, not only as consumers but also producers of healthcare, is a rather formidable and complex cultural change to be addressed.

The Migration-Crime Nexus and the Press in France, Germany, and the United Kingdom

2018 ◽  
Vol 15 (2) ◽  
pp. 167-181
Author(s):  
Alexander A Caviedes
Keyword(s):  
United Kingdom ◽  
Human Trafficking ◽  
Organized Crime ◽  
Steady Increase ◽  
Press Coverage ◽  
Individual Country ◽  
The United Kingdom ◽  
The Press ◽  
And Migration ◽  
Over Time

This article explores the link between migrants and crime as portrayed in the European press. Examining conservative newspapers from France, Germany, and the United Kingdom from 2007 to 2016, the study situates the press coverage in each individual country within a comparative perspective that contrasts the frequency of the crime narrative to that of other prominent narratives, as well as to that in the other countries. The article also charts the prevalence of this narrative over time, followed by a discussion of which particular aspects of crime are most commonly referenced in each country. The findings suggest that while there has been no steady increase in the coverage of crime and migration, the press securitizes migration by focusing on crime through a shared emphasis on human trafficking and the non-European background of the perpetrators. However, other frames advanced in these newspapers, such as fraud or organized crime, comprise nationally distinctive characteristics.

scholarly journals Data-Driven Analysis on Inter-City Commuting Decisions in Germany

2021 ◽  
Vol 13 (11) ◽  
pp. 6320
Author(s):  
Hui Chen ◽  
Sven Voigt ◽  
Xiaoming Fu
Keyword(s):  
Good Accuracy ◽  
Housing Price ◽  
Machine Learning Algorithms ◽  
Data Driven ◽  
Steady Increase ◽  
Time Duration ◽  
Major Bottleneck ◽  
Potential Factors ◽  
Commuting Patterns ◽  
Industry Sectors

Understanding commuters’ behavior and influencing factors becomes more and more important every day. With the steady increase of the number of commuters, commuter traffic becomes a major bottleneck for many cities. Commuter behavior consequently plays an increasingly important role in city and transport planning and policy making. Although prior studies investigated a variety of potential factors influencing commuting decisions, most of them are constrained by the data scale in terms of limited time duration, space and number of commuters under investigation, largely owing to their dependence on questionnaires or survey panel data; as such only small sets of features can be explored and no predictions of commuter numbers have been made, to the best of our knowledge. To fill this gap, we collected inter-city commuting data in Germany between 1994 and 2018, and, along with other data sources, analyzed the influence of GDP, housing and the labor market on the decision to commute. Our analysis suggests that the access to employment opportunities, housing price, income and the distribution of the location’s industry sectors are important factors in commuting decisions. In addition, different age, gender and income groups have different commuting patterns. We employed several machine learning algorithms to predict the commuter number using the identified related features with reasonably good accuracy.

scholarly journals On the Experimental, Numerical and Data-Driven Methods to Study Urban Flows

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1310
Author(s):  
Pablo Torres ◽  
Soledad Le Clainche ◽  
Ricardo Vinuesa
Keyword(s):  
Physical Phenomenon ◽  
Urban Pollution ◽  
Pollutant Dispersion ◽  
Urban Environments ◽  
Machine Learning Algorithms ◽  
Data Driven ◽  
Thermal Fields ◽  
Use Of Data ◽  
Sustainability Challenges ◽  
New Research

Understanding the flow in urban environments is an increasingly relevant problem due to its significant impact on air quality and thermal effects in cities worldwide. In this review we provide an overview of efforts based on experiments and simulations to gain insight into this complex physical phenomenon. We highlight the relevance of coherent structures in urban flows, which are responsible for the pollutant-dispersion and thermal fields in the city. We also suggest a more widespread use of data-driven methods to characterize flow structures as a way to further understand the dynamics of urban flows, with the aim of tackling the important sustainability challenges associated with them. Artificial intelligence and urban flows should be combined into a new research line, where classical data-driven tools and machine-learning algorithms can shed light on the physical mechanisms associated with urban pollution.

Railway crossing vertical vibration response prediction using a data-driven neuro-fuzzy model – Influence of train factors

2021 ◽  
pp. 095440972098666
Author(s):  
Kaveh Mehrzad ◽  
Shervan Ataei
Keyword(s):  
Model Comparison ◽  
Selection Process ◽  
Fuzzy Model ◽  
Response Prediction ◽  
Vibration Response ◽  
Vibration Monitoring ◽  
Data Driven ◽  
Steady Increase ◽  
Neuro Fuzzy ◽  
Railway Crossing

This paper provides a data-driven model of the vibration response of a railway crossing during vehicle passages. Many of the features of trains passing through instrumented crossing are extracted from measured data. Based on the feature selection process, speed, dynamic axle load and the number of wagons are found proper inputs in the prediction model. Train-crossing interaction response at a crossing due to passing trains is modeled from a data-driven Neuro-Fuzzy soft computing approach. Locally Linear Model Tree (LOLIMOT) is applied to predict the crossing nose acceleration. The model comparison against measurements shows that the ability to predict the extrapolation cases at off-range speeds has satisfactory compatibility. The monitored passing trains are ranked based on the LOLIMOT input space dimension cuts and extrapolation of the model up to higher train speeds. The influence of train factors (i.e. speed, dynamic axle load, number of wagons) on crossing response is demonstrated. Also, based on the analysis results, it is concluded that with a steady increase in train speeds, some trains show a greater amplification in vibration response than others. The results can be applied in data processing in the crossing vibration monitoring and detection of trains with crossing impact sensitive to speed increasing that can lead to proper operation policies to reduce damages and maintenance costs.

‘Safety first’ versus ‘op de barricaden’

2014 ◽  
Vol 42 (4) ◽  
Author(s):  
Jelle W. Boumans ◽  
Rens Vliegenthart
Keyword(s):  
Content Analysis ◽  
The Netherlands ◽  
News Media ◽  
Nuclear Energy ◽  
Critical Assessment ◽  
Regional Newspapers ◽  
National Newspaper ◽  
Definition Of ◽  
Regional Newspaper ◽  
Safety First

‘Safety first’ versus ‘fighting on the barricades’: a content analysis of the nuclear debate in the Netherlands ‘Safety first’ versus ‘fighting on the barricades’: a content analysis of the nuclear debate in the Netherlands News content is often the result of an intense struggle between sources over the definition of an issue. This study content analyzes the agendas of the proponents and antagonists of nuclear energy in the Netherlands between 2002-2012 and investigates to what extent these agendas overlap with the news media agendas, including the often overlooked press agencies and regional newspapers. Analysis shows that the agenda of opponent Greenpeace – consisting of the themes of nuclear waste and risks – is slightly more visible in news agency and national newspaper content. Regional newspapers however tend to adopt the nuclear industry’s most dominant theme – safety. Interestingly enough, one regional newspaper seems to completely ignore the oppositional voice. This finding calls for a critical assessment of the relation between regional newspaper content and information subsidies.

scholarly journals A general pattern in the construction of economic newsworthiness? Analyzing news factors in popular, quality, regional, and financial newspapers

Journalism ◽  
2017 ◽  
Vol 21 (2) ◽  
pp. 279-300 ◽  
Author(s):  
Mark Boukes ◽  
Rens Vliegenthart
Keyword(s):  
Content Analysis ◽  
Large Scale ◽  
General Pattern ◽  
Geographical Proximity ◽  
Detailed Understanding ◽  
Economic News ◽  
Regional Newspapers ◽  
Different Types

Journalists use news factors to construct newsworthy stories. This study investigates whether different types of news outlets emphasize different news factors. Using a large-scale manual content analysis ( n = 6489), we examine the presence of seven news factors in economic news across four different outlets types (i.e. popular, quality, regional, and financial newspapers). Results suggest that popular and regional newspapers particularly rely on the news factors of personification, negativity, and geographical proximity. Quality newspapers, instead, employ a rather general pattern of news factors, whereas the financial newspaper consistently relies on less news factors in its reporting. Findings urge scholars to move toward a more detailed understanding of how newsworthiness is constructed in different types of news outlets.

scholarly journals Content analysis for <i>Agricultural Records</i> of the United Kingdom, AD 200 to 1977: a study of frequency in human records concerning climate phenomenon

2011 ◽  
Vol 7 (4) ◽  
pp. 2555-2577
Author(s):  
D. H. Holt
Keyword(s):  
Content Analysis ◽  
Ice Age ◽  
Climate Data ◽  
The United Kingdom ◽  
Weather Phenomenon ◽  
Continuous Record ◽  
Frequency Occurrence ◽  
The Uk ◽  
Climate Events

Abstract. A content analysis has been completed on a text from the UK that has gathered agricultural and climate data from the years AD 220 to 1977 from 100s of sources. The content analysis coded all references to climate and agriculture to ascertain which climate events were recorded and which were not. This study addressed the question: is there bias in human records of climate? This evaluated the continuous record (AD 1654–1977), discontinous record (AD 220–1653), the whole record (AD 220–1977), the Little Climate Optimum (AD 850–1250) and the Little Ice Age (AD 1450–1880). This study shows that there is no significant variation in any of these periods in frequency occurrence of "good" or "bad" climate suggesting humans are not recording long-term changes in climate, but they are recording weather phenomenon as it occurs.

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