All work and no play: A text analysis

2019 ◽  
Vol 61 (3) ◽  
pp. 236-251 ◽  
Author(s):  
Kate Downer ◽  
Chrissie Wells ◽  
Charlotte Crichton
Keyword(s):  
Natural Language ◽  
Survey Data ◽  
Text Analysis ◽  
Market Research ◽  
Human Error ◽  
Automated Analysis ◽  
Text Analytics ◽  
Scalar Data ◽  
Over Time

Automated analysis of open-ended text survey data is an appealing prospect. It eliminates human error and human variability and can be used to create models that are easier to update over time than a manual approach to coding generally yields. Today, text analytics is a huge business and is among the most popular innovations within the current research landscape. However, within the research industry, there has been little change in usage in recent years, and awareness of the options available appears to be limited. We wished to look more closely at the true strengths of different approaches, the main barriers to their adoption, and how these might be overcome. Using text responses from a short survey about work and play in two markets, we contrasted two tools in analyzing the output: Q’s text analysis component and Google Cloud Natural Language. We chose these tools as they can each be easily applied to survey data but are based on different analytic principles. We found some surprising differences between the output of the two tools and between the text analysis metrics and scalar data. We conclude by discussing some of the key contemporary themes in text analytics and the likely future role of this method within market research and insight.

scholarly journals The Reciprocal Involvement of Family Business Owners and Communities in Business Success

2020 ◽  
Vol 12 (10) ◽  
pp. 4048
Author(s):  
Jennifer Johnson Jorgensen ◽  
Diane Masuo ◽  
Linda Manikowske ◽  
Yoon Lee
Keyword(s):  
Survey Data ◽  
Family Business ◽  
Business Owners ◽  
Business Success ◽  
Community Sustainability ◽  
Community Members ◽  
Business Outcomes ◽  
Rare Group ◽  
Over Time

It is believed that highly involved business owners and community members will yield benefits to ensure business and community sustainability over time. However, little research has delved into understanding the role of business owners’ involvement and the community’s involvement in business outcomes. Thus, the purpose of this study was to investigate the reciprocal involvement of family business owners and the community. To investigate this phenomenon, this study utilized survey data from a rare group of business owners who currently operate long-standing businesses. Results indicate that more involved business owners perceived higher levels of business success. When seeking a profit, business owners also tended to be more involved in the community than owners not seeking a profit. However, family-owned businesses felt that the community did not contribute to their businesses and did not stay involved over time. Overall, business owners felt that they contributed more than the community provided in return. Recommendation is made to stress in entrepreneurship curricula the importance of reciprocal involvement between businesses and their communities and vice versa to promote business and community sustainability over time.

scholarly journals Online self-expression and experimentation as ‘reflectivism’: Using text analytics to examine the participatory forum Hello Sunday Morning

2016 ◽  
Vol 21 (2) ◽  
pp. 119-135 ◽  
Author(s):  
Nicholas Carah ◽  
Carla Meurk ◽  
Daniel Angus
Keyword(s):  
Health Promotion ◽  
New Media ◽  
Text Analysis ◽  
Critical Appraisal ◽  
Health Interventions ◽  
Text Analytics ◽  
Sunday Morning ◽  
Media Technologies ◽  
Cultural Terms ◽  
Over Time

Hello Sunday Morning is an online health promotion organisation that began in 2009. Hello Sunday Morning asks participants to stop consuming alcohol for a period of time, set a goal and document their progress on a personal blog. Hello Sunday Morning is a unique health intervention for three interrelated reasons: (1) it was generated outside a clinical setting, (2) it uses new media technologies to create structured forms of participation in an iterative and open-ended way and (3) participants generate a written record of their progress along with demographic, behavioural and engagement data. This article presents a text analysis of the blog posts of Hello Sunday Morning participants using the software program Leximancer. Analysis of blogs illustrates how participants’ expressions change over time. In the first month, participants tended to set goals, describe their current drinking practices in individual and cultural terms, express hopes and anxieties and report on early efforts to change. After month 1, participants continued to report on efforts to change and associated challenges and reflect on their place as individuals in a drinking culture. In addition to this, participants evaluated their efforts to change and presented their ‘findings’ and ‘theorised’ them to provide advice for others. We contextualise this text analysis with respect to Hello Sunday Morning’s development of more structured forms of online participation. We offer a critical appraisal of the value of text analytics in the development of online health interventions.

scholarly journals Approaches to Text Analysis

2019 ◽  
Vol IV (I) ◽  
pp. 1-7
Author(s):  
Mark Perkins
Keyword(s):  
Artificial Intelligence ◽  
Natural Language ◽  
Text Analysis ◽  
The Other ◽  
Computational Approaches ◽  
Future Developments ◽  
Broad Term ◽  
Over Time

Text Analysis is a broad term that covers many approaches and technologies. Those initially stemming from the academic sphere have come to enter the commercial, and today there is a wide interplay between the two. A further dichotomy is that between natural language and computational approaches. Over time, approaches have come to draw upon each other, although there are still clear dividing lines and practitioners tend to rely mainly on one approach or the other. This paper seeks to draw out these approaches and give an account of them over time. It also points to future developments where artificial intelligence is increasingly used.

scholarly journals Role of Deep Recurrent Neural Networks in Natural Language Processing

2019 ◽  
Vol 8 (2S11) ◽  
pp. 4082-4084
Keyword(s):  
Neural Networks ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Recurrent Neural Networks ◽  
Text Analysis ◽  
Human Language ◽  
Present Information ◽  
Hierarchical Representations

Deep learning methods are used to study hierarchical representations of data. Natural Language Processing is a group of computing methodologies used for analyzing and illustrating of Natural Language (NL). Natural Language is used to collect and present information in numerous fields. NLP can be to extract and process information in human language automatically. This paper is to highlight vital research contributions in text analysis, classification and extracting useful information using NLP

scholarly journals Data Science Opportunities at Central Banks: Overview

2020 ◽  
pp. 13-24
Author(s):  
Dmytro Krukovets
Keyword(s):  
Social Networks ◽  
Text Analysis ◽  
Data Science ◽  
Central Banks ◽  
Central Banking ◽  
Use Cases ◽  
Financial Forecasting ◽  
National Bank ◽  
Over Time

This paper reviews the main streams of Data Science algorithm usage at central banks and shows their rising popularity over time. It contains an overview of use cases for macroeconomic and financial forecasting, text analysis (newspapers, social networks, and various types of reports), and other techniques based on or connected to large amounts of data. The author also pays attention to the recent achievements of the National Bank of Ukraine in this area. This study contributes to the building of the vector for research the role of Data Science for central banking.

What Is Happening to Caste? A View from Some North Indian Villages

2003 ◽  
Vol 62 (4) ◽  
pp. 1171-1193 ◽  
Author(s):  
Anirudh Krishna
Keyword(s):  
Survey Data ◽  
National Level ◽  
Building Blocks ◽  
Considerable Change ◽  
Political Organization ◽  
Community Leaders ◽  
Indian Politics ◽  
Political Outcomes ◽  
Over Time

The role of caste in indian politics is undergoing considerable change. Caste and patron-client links have been regarded traditionally as the building blocks of political organization in India (Brass 1994; Manor 1997; Migdal 1988; Kothari 1988; Weiner 1967), and vertical and horizontal mobilizations by patrons and caste leaders, respectively, have been important influences on political outcomes (Rudolph and Rudolph 1967). There are indications, however, that the influence of patronage and caste might have declined considerably in recent years:[National-level] survey data reveal some important facts that run counter to the conventional wisdom on voter behavior. … In 1996, 75 percent of the sample said they were not guided by anyone in their voting decision. … Of the 25 percent who sought advice, only 7 percent sought it from caste and community leaders … that is, less than 2 percent of the electorate got direct advice on how to vote from caste and community leaders. … The most important survey data show the change over time. In 1971, 51 percent of the respondents agreed that it was “important to vote the way your caste/community does” (30 percent disagreed), but in 1996 the percentages were reversed: 51 percent disagreed with that statement (29 percent agreed). … In 1998, “caste and community” was seen as an issue by only 5.5 percent of the respondents in one poll … and [it] ranked last of nine issues in another. All the evidence points to the fact that these respondents are correct: members of particular castes … can be found voting for every party. … It is less and less true that knowing the caste of a voter lets you reliably predict the party he or she will vote for.(Oldenburg 1999, 13–15, emphasis in original)

DARR: A Free-text Analysis System for the Automatic Documentation of Radiological Reports

1977 ◽  
Vol 16 (03) ◽  
pp. 144-153 ◽  
Author(s):  
E. Vaccari ◽  
W. Delaney ◽  
A. Chiesa
Keyword(s):  
Natural Language ◽  
Text Analysis ◽  
Automatic Documentation ◽  
Free Text ◽  
Software System ◽  
Automatic Translation ◽  
Radiological Report ◽  
Analysis System ◽  
Content Processing

A software system for the automatic free-text analysis and retrieval of radiological reports is presented. Such software involves: (1) automatic translation of the specific natural language in a formalized metalanguage in order to transform the radiological report in a »normalized report« analyzable by computer; (2) content processing of the normalized report to select desired information. The approach used to accomplish point (1) is described in detail referring to a specific application.

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