research papers on data journalism

Although data journalism is practiced globally, data journalism research has traditionally focused on a limited set of countries where scholars study developments in their own environment. Many recently published studies illustrate a growing scholarly interest in data journalism beyond the liberal and democratic corporatist media system, but ...

This article surveys and compares literature on data journalism from two areas of inquiry: journalism studies and visualization research. As digital interfaces become an important access point for ...

Anderson (2013) suggested 'six approaches to a sociology of computational journalism' (p. 1010), outlining a framework to investigate a phenomenon that, until then, had been explored primarily by computer scientists and practitioners active in the field. His proposal seemed driven by a discontent with the 'internalist tendencies at [the] early stage of academic research' (p. 1007) that ...

Journalism and Media is an international peer-reviewed open access quarterly journal published by MDPI. Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good ...

Data-driven journalism (DDJ) can be considered as journalism's response to the datafication of society. To better understand the key components and development of this still young and fast evolving genre, we investigate what the field itself defines as its 'gold-standard': projects that were nominated for the Data Journalism Awards (DJA) from 2013 to 2016 (n= 225).

data journalism; data-driven journalism; data visualisation; data visualization; digital preservation; digital archiving; software preservation Introduction "Journalism is the first rough draft of history" (widely attributed to Philip Graham, 1963), and the archives of news organisations are an indispensable source for research into global ...

The main goal of this study is to investigate the state of art of data journalism research regarding its process as stated in the "inverted pyramid of data journalism". Therefore, we designed the research questions as follows: ... Most of the papers discussed data journalism concepts, showing that this field is a new subject, still under ...

Following this trend, this paper presents a research literature analysis on the role of Data Science (DS) in Digital Journalism (DJ). Specifically, the aim is to present a critical literature review, synthetizing the main application areas of DS in DJ, highlighting research gaps, challenges, and opportunities for future studies.

The term data journalism is a relatively new term, with fewer than 10 years of history, and an even shorter history in academic literature. In an analysis of data journalism literature,Ausserhofer et al.(2017) suggest an increase in research publications on data journalism and related fields since 2010. They report

Special attention is given to Web 3.0 and open data that can play an important role in data journalism. A survey conducted among professional journalists in Greece concerning data journalism is ...

This paper analyses the discursive practices that have constructed data journalism as an accepted way to talk about quantitative, computational approaches to newswork (Coddington, 2019).I analyse the expert talk of the field's pioneers using Foucault's (1981) distinctive concept of discourse to uncover the power relations woven into data journalism's optimistic language.

TLDR. This paper presents the initial results of a two-year research project, the Data Journalism Work Practices, which focuses on newsrooms in Finland, UK and US, and claims that there are already at least three different models for organizing data journalism work practices, and two main streams of data journalism. 54.

Published: March 23, 2021. ISBN: 9789048542079. This book offers an interdisciplinary introduction to data journalism, offering a unique combination of critical reflection and practical insight into the field, including how data journalism is done around the world and the broader consequences of datafication in the news.

Data journalism is a type of journalism that reflects the increasing role that digital data uses in the production and distribution of information in the digital age [].It reflects the increased interaction between content producers (journalists) and many other fields such as design, computer science and statistics [].From the journalists' point of view, it represents "an overlapping set ...

This paper, therefore, seeks to add to the scant systematic review in the field by systematically reviewing the literature on data journalism as a contribution to the scant literature. More so ...

To date, much of the research on data narration and storytelling has been in the field of data journalism [8,9, 10, 11,12]. After reviewing the peer-reviewed literature relating to our research ...

As the media landscape continuously evolves in response to the increasing dominance of data, it is important to understand how future journalists perceive and respond to the emerging discipline of data journalism. This paper explores the impact of an introductory session on data journalism conducted with second-year journalism students at Aristotle University, Thessaloniki, Greece. The study ...

Data journalism is based on data used both as a source of a story and as a proof for facts stated in journalistic investigations. Core principles of journalistic work are changing under the influence of data: working with data, acquiring datasets, verifying data, analyzing and presenting it in data stories is drastically different from traditional journalistic methods, while simultaneously ...

This is a research paper that was presented at the Global Investigative Journalism Conference 2017 Academic Track, which IJEC organized and covered. University professor and database journalism specialist Milagros Salazar researches the role of data in journalism, its potentials and limits. "Journalism is full of data, but not everything is data journalism. There is a difference between using ...

Features Fact Sheets Videos Data Essays. Research Topics . Topics. ... This is the latest report in Pew Research Center's ongoing investigation of the state of news, information and journalism in the digital age, a research program funded by The Pew Charitable Trusts, with generous support from the John S. and James L. Knight Foundation. ...

In comparison, Mathematics papers and the Nature portfolio showed the least LLM modification (up to 6.3%). Moreover, at an aggregate level, our analysis reveals that higher levels of LLM-modification are associated with papers whose first authors post preprints more frequently, papers in more crowded research areas, and papers of shorter lengths.

View PDF Abstract: In the domain of data science, the predictive tasks of classification, regression, and imputation of missing values are commonly encountered challenges associated with tabular data. This research endeavors to apply Large Language Models (LLMs) towards addressing these predictive tasks. Despite their proficiency in comprehending natural language, LLMs fall short in dealing ...

Most of the available research on data journalism has generally focused on a limited set of countries in the Global North (Appelgren et al., 2019; Fink and Anderson, 2015; Larrondo-Ureta and Ferreras-Rodríguez, 2021). Research on data journalism in Africa is still emerging, as outlined earlier in the paper.

We trained a 7B model on 1T tokens (called DBRX Dense-A) using the DBRX pretraining data. It reached 39.0% on the Databricks Gauntlet compared to 30.9% for MPT-7B. We estimate that our new pretraining data is at least 2x better token-for-token than the data used to train MPT-7B.

The integration and deployment of large language model (LLM)-based intelligent agents have been fraught with challenges that compromise their efficiency and efficacy. Among these issues are sub-optimal scheduling and resource allocation of agent requests over the LLM, the difficulties in maintaining context during interactions between agent and LLM, and the complexities inherent in integrating ...

To our knowledge, no previous research gathered data at this scale (250 samples, 226 chemical parameters, 50 sensory attributes and 5 consumer scores) to disentangle and validate the chemical ...

This paper examines potential bias in the Census Household Composition Key's (CHCK) probabilistic parent-child linkages. By linking CHCK data to the American Community Survey (ACS), we reveal disparities in parent-child linkages among specific demographic groups and find that characteristics of children that can and cannot be linked to the CHCK vary considerably from the larger population.