scholarly journals Using big data for impact evaluations

10.51744/cmb2 ◽  
2021 ◽  
Author(s):  
Francis Rathinam ◽  
◽  
P Thissen ◽  
M Gaarder

The amount of big data available has exploded with recent innovations in satellites, sensors, mobile devices, call detail records, social media applications, and digital business records. Big data offers great potential for examining whether programmes and policies work, particularly in contexts where traditional methods of data collection are challenging. During pandemics, conflicts, and humanitarian emergency situations, data collection can be challenging or even impossible. This CEDIL Methods Brief takes a step-by-step, practical approach to guide researchers designing impact evaluations based on big data. This brief is based on the CEDIL Methods Working Paper on ‘Using big data for evaluating development outcomes: a systematic map’.

2018 ◽  
Vol 03 (03) ◽  
pp. 1850003 ◽  
Author(s):  
Jared Oliverio

Big Data is a very popular term today. Everywhere you turn companies and organizations are talking about their Big Data solutions and Analytic applications. The source of the data used in these applications varies. However, one type of data is of great interest to most organizations, Social Media Data. Social Media applications are used by a large percentage of the world’s population. The ability to instantly connect and reach other people and companies over distributed distances is an important part of today’s society. Social Media applications allow users to share comments, opinions, ideas, and media with friends, family, businesses, and organizations. The data contained in these comments, ideas, and media are valuable to many types of organizations. Through Data Mining and Analysis, it is possible to predict specific behavior in users of the applications. Currently, several technologies aid in collecting, analyzing, and displaying this data. These technologies allow users to apply this data to solve different problems, in different organizations, including the finance, medicine, environmental, education, and advertising industries. This paper aims to highlight the current technologies used in Data Mining and Analyzing Social Media data, the industries using this data, as well as the future of this field.


2021 ◽  
Author(s):  
◽  
Travis Christensen

<p>This study analyses the effects of Big Data visualisations on jurors’ decisions in audit litigation cases. Specifically, the study investigates the effects of different types of Big Data visualisations (word clouds or bar graphs) and different sources of Big Data (emails or social media posts) on jurors’ perceptions of auditors’ work and the size of the negligence awards that jurors recommend. The study theorises that the emotions elicited and the reliability of the data used to create visualisations such as word clouds will have dramatic effects on jury verdicts in audit negligence trials. There is considerable literature to support this assertion. However, after data collection, it was discovered that jurors are not influenced by the emotions elicited by visualisations. Rather, participants were very sceptical of more novel types of visualisations, such as word clouds, but could be persuaded by the inherent emotions elicited and the reliability of the data if they found the visualisation useful.</p>


This edited collection tackles subjects that have arisen as a result of new capabilities to collect, analyse and use vast quantities of data using complex algorithms. Questions tackled include what is wrong with targeted advertising in political campaigns, whether echo chambers really are a matter of genuine concern, what is the impact of data collection through social media and other platforms on questions of trust in society and is there a problem of opacity as decision-making becomes increasingly automated? The contributors consider potential solutions to these challenges and discuss whether an ethical compass is available or even feasible in an ever more digitized and monitored world. The editors bring together original research on the philosophy of big data and democracy from leading international authors, with recent examples and case references – including the 2016 Brexit Referendum, the Leveson Inquiry and the Edward Snowden leaks – and combine them in one authoritative volume at time of great political turmoil.


Author(s):  
Ernest W. Brewer ◽  
Geraldine Torrisi-Steele ◽  
Victor C. X. Wang

Survey research, in various forms, is the mainstay for social researchers and anyone interested in finding out about people's opinions, attitudes, beliefs, and experiences. Survey research evolved from simple data collection to a more sophisticated scientific method and has proved useful in describing various aspects of the human condition as a basis for further action. However, now survey research is being challenged by the digital world as defined by big data, social media, and mobile devices. In the chapter, the authors provide a historical perspective on survey research, along with a brief presentation of foundational elements of survey research. Then, with the intent of evoking reflective discussion, the authors identify some of the core issues and viewpoints surrounding survey research in the present digital world.


Author(s):  
Shaila S. G. ◽  
Monish L. ◽  
Lavanya S. ◽  
Sowmya H. D. ◽  
Divya K.

The new trending technologies such as big data and cloud computing are in line with social media applications due to their fast growth and usage. The big data characteristic makes data management challenging. The term big data refers to an immense collection of both organised and unorganised data from various sources, and nowadays, cloud computing supports in storing and processing such a huge data. Analytics are done on huge data that helps decision makers to take decisions. However, merging two conflicting design principles brings a challenge, but it has its own advantage in business and various fields. Big data analytics in the cloud places rigorous demands on networks, storage, and servers. The chapter discusses the importance of cloud platform for big data, importance of analytics in cloud and gives detail insight about the trends and techniques adopted for cloud analytics.


Author(s):  
Bhavani Thuraisingham ◽  
Mohammad Mehedy Masud ◽  
Pallabi Parveen ◽  
Latifur Khan

The paper investigates the effect of technology-based applications on brand image in the telecommunications industry. The study aims to identify the most influencing technology-based application on brand image and areas of improvements for each application. The study proposes a model that shows the effect of certain applications on brand image in the telecommunications industry. A quantitative survey was used for data collection to support the model. The research shows a significant overall model where technology-based applications account for 28% of variance in the consumer’s perception of the brand image. Websites and social media applications have significant impact on brand image while mobile applications & services have positive but insignificant impact on brand image. The paper can help companies to adopt technology-based applications in their brand management strategies and invest more on technology-based channels to enhance the brand image, attract more customers, and gain competitive advantage. There has been little research focusing on the effect of technology-based applications on the brand image and specifically in the telecommunications industry.


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