Easy-to-read Meets Accessible Web in the E-government Context

In the e-government context, content of information and service systems needs to be accessible and easy-to-read. E-government systems are increasingly self-service systems. If the content of these systems is incomprehensible, citizens are not able to exercise their rights or fulfill their duties. Comprehensibility, however, is more than just providing text that is easy to read. The ease-of-understanding of a text is a result of the interplay between content characteristics, reader characteristics and task/context characteristics, as is the case for usability. This multi-faceted form of accessibility cannot be assessed and evaluated with just the existing easy-to-read guidelines. Measuring ease-of-understanding, which is a legal requirement for e-government systems and other public services, requires a process-oriented approach besides the currently available product-oriented easy-to-read guidelines

Effects of user expectations on website information comprehension and satisfaction, The

2014 Summer.Includes bibliographical references.The purpose of this qualitative study was to examine the role of users' expectations of a website information search in determining their comprehension of the information on a website and their satisfaction with the website. Interviews to determine their satisfaction with the website and think-aloud sessions were employed to gather data from participants, and open coding was used to analyze responses. The findings of this study support the previous literature on scripts with respect to the usability of the Veterans Affairs website. The study found that scripts are present before users search for information on a website. Those scripts provide users with a strategy to find needed information efficiently, but when a website fails to conform to a user's script, users experience a more difficult search and lower satisfaction with the website. More research into the particular scripts that inform users website searching strategies will help to encourage better communication on websites. Adhering to the Plain Writing Act (2010) will improve communication on the Veterans Affairs website

Dr. Google: what about the human papillomavirus vaccine?

To assess and analyze the information and recommendations provided by Google Web Search™ (Google) in relation to web searches on the HPV vaccine, indications for females and males and possible adverse effects.|In the comprehensive analysis of results, 72.2% of websites offer information favorable to HPV vaccination, with varying degrees of content detail, vs. 27.8% with highly dissuasive content in relation to HPV vaccination. The most frequent type of site is the blog or forum. The information found is frequently incomplete, poorly structured, and often lacking in updates, bibliography and adequate citations, as well as sound credibility criteria (scientific association accreditation and/or trust mark system).|Descriptive cross-sectional study of the results of 14 web searches. Comprehensive analysis of results based on general recommendation given (favorable/dissuasive), as well as compliance with pre-established criteria, namely design, content and credibility. Sub-analysis of results according to site category: general information, blog / forum and press.|Google, as a tool which users employ to locate medical information and advice, is not specialized in providing information that is necessarily rigorous or valid from a scientific perspective. Search results and ranking based on Google's generalized algorithms can lead users to poorly grounded opinions and statements, which may impact HPV vaccination perception and subsequent decision making

Investigating the effects of controlled language on the reading and comprehension of machine translated texts: A mixed-methods approach

This study investigates whether the use of controlled language (CL) improves the readability and comprehension of technical support documentation produced by a statistical machine translation system. Readability is operationalised here as the extent to which a text can be easily read in terms of formal linguistic elements; while comprehensibility is defined as how easily a text’s content can be understood by the reader. A biphasic mixed-methods triangulation approach is taken, in which a number of quantitative and qualitative evaluation methods are combined. These include: eye tracking, automatic evaluation metrics (AEMs), retrospective interviews, human evaluations, memory recall testing, and readability indices. A further aim of the research is to investigate what, if any, correlations exist between the various metrics used, and to explore the cognitive framework of the evaluation process. The research finds that the use of CL input results in significantly higher scores for items recalled by participants, and for several of the eye tracking metrics: fixation count, fixation length, and regressions. However, the findings show slight insignificant increases for readability indices and human evaluations, and slight insignificant decreases for AEMs. Several significant correlations between the above metrics are identified as well as predictors of readability and comprehensibility

A Topic Recommender for Journalists

The way in which people acquire information on events and form their own opinion on them has changed dramatically with the advent of social media. For many readers, the news gathered from online sources become an opportunity to share points of view and information within micro-blogging platforms such as Twitter, mainly aimed at satisfying their communication needs. Furthermore, the need to deepen the aspects related to news stimulates a demand for additional information which is often met through online encyclopedias, such as Wikipedia. This behaviour has also influenced the way in which journalists write their articles, requiring a careful assessment of what actually interests the readers. The goal of this paper is to present a recommender system, What to Write and Why, capable of suggesting to a journalist, for a given event, the aspects still uncovered in news articles on which the readers focus their interest. The basic idea is to characterize an event according to the echo it receives in online news sources and associate it with the corresponding readers’ communicative and informative patterns, detected through the analysis of Twitter and Wikipedia, respectively. Our methodology temporally aligns the results of this analysis and recommends the concepts that emerge as topics of interest from Twitter and Wikipedia, either not covered or poorly covered in the published news articles