News Archives Research Articles

Digital Archiving and Access to Print Media Resources: A Study among Leading Malayalam Newspaper Libraries in Kerala

A newspaper library is a significant provider of various information sources needed for the media professionals. Librarians working in newspaper libraries have to play an outstanding role to pace with the changing scenario. The transformation of newspaper archives from print to digital is a noteworthy initiative by newspaper libraries. The paper presents a digital archiving initiative by newspaper libraries. It points out the need, purpose, and advantages of digital news archives. The paper also highlights the IT infrastructure facilities used and shares the challenges faced by librarians in the process of digital archiving.

Similarity matching in news articles

With the need for intelligence growing every day, big data analytics has become the forefront of intelligence work. Having the ability to access news archives and other news article databases have ...

Sustaining television news archives

This paper reports on the findings of a sustainability study of television news archives conducted in 2018. After reviewing the history of the Vanderbilt Television News Archive, the paper discusses the questions raised by the sustainability project. What are the legal, economic, and technical issues that archivists need to consider when preserving television news, making their collections accessible to the public, and allowing researchers to explore their holdings through emerging technologies like data and text mining? The second half of the paper considers ways that nonprofit television news archives might collaborate more closely. While sharing and aggregating standardised metadata would constitute a promising step toward that goal, the paper highlights three other potential avenues of coordination. First, the legal basis for data mining nonprofit video archives should be clarified in order to meet the growing demand among researchers for this mode of computational inquiry. Second, on a technical level, broader adoption of descriptive metadata with full-text transcriptions would make it easier to analyse collections with machine learning and artificial intelligence. Finally, the sustainability of nonprofit television news archiving over the longterm requires acknowledgment and accommodation of the diversity of publics that these archives serve as well as of their distinctive financial models.

African Americans and Unions in Los Angeles

This paper highlights the racism that permeated Labor Unions across Los Angeles while determining the methods that African American men and women employed in order to successfully lobby not only the unions themselves but the United States government in cases where the locals were unwilling to integrate. I came upon this topic after a story I had heard at family gatherings about an ancestor of mine, William Schneiderman, who was a union leader, outspoken communist, and whose similarities to Harry Bridges called my attention to Los Angeles unions in my new hometown of San Pedro. My focus on race relations within L.A. unions which eventually led me to focus on African Americans and Los Angeles organized labor given their more vocal activism in the city, more so than any other ethnic group. Black workers fought the unions they came to be a part of for their rights as union members and faced belligerent racism constantly. In the course of my research, I located archival records from numerous repositories across L.A., including the Los Angeles Times Historical Archive, the Long Beach Library Historical Archives, the Random Lengths News Archives, the National Archives and Records Administration’s ????les, and the International Longshoremen’s and Warehousemen’s Union’s Special Collections and Archives.

OCR correction for Indonesian historic newspapers using word repetition, stemmer and n-gram

Most digital archives of the old newspapers in Indonesia are only available as microfilm image file without their textual content. Manual transcription is certainly not effective and tiring for publishers that have large archives. Therefore, more automated transcription is required. As a part of that effort, this paper proposes OCR error correction of old spelling news articles utilizing new spelling databases. Spelling conversions which based on pattern are used to bridge spelling differences. The Error detection uses dictionary lookup and the phenomenon of word repetition and OCR errors that mostly are non-word errors. The Dictionary is built from KBBI and enriched with derivative words, English words, and entity names from validated news archives. Confix-stripping stemmer is used to validate derivative words while the English dictionary is used to validate English words in the news archive. The Error correction uses context-based methods by searching the phrase trigram/bigram word for each error in Google, then the Google Spelling suggestions are used as the correction. Experiments on 9 texts of OCR result of KOMPAS daily article between 1965 and 1966 is resulting the comparison of error rate before and after the correction (improvement ratio) of 193.01% compared to Hunspell spell checker of 61.47%.

Dialogic contractions in online news discourse on violence against women in Nigeria

ABSTRACTThe paper analyses dialogic contractions in selected online news discourse on Violence against Women (henceforth, VAW) in Nigeria. The data comprise ten (10) purposively selected online news reports on various cases of VAW sourced from the news archives of Saharareporters.com; NigeriaFilms.com; Premium Times; and The Punch Online. The study selects only cases of VAW in Nigeria. The study performs a qualitative analysis of the online news discourses from White’s dialogic perspectives of intersubjective positioning. The analysis portrays diverse linguistic resources through which online news reporters and commenters firstly acknowledge, and then, restrict the scope of diogic alternatives in various communicative contexts in the reportage of cases of VAW in Nigeria; the dialogistic functions of the identified resources of dialogic contractions; and their rhetorical effects with respect to audience (dis)alignment. The paper, therefore, concludes that the dialogic theory enhances the understanding on how online audience and their assumed shared societal values/beliefs on VAW in the Nigerian context are taken as important and foregrounded in the creation of online news discourse on VAW.

Digging Deeply in Catholic Studies

This paper introduces the work of the Catholic Research Resources Alliance (CRRA), a non-profit organization comprising fifty Catholic colleges, universities, seminaries, and religious congregations. In service to its mission "to provide enduring access to Catholic research resources in the Americas," the CRRA has launched two significant initiatives of freely available and collaboratively curated content: the Catholic Portal and the Catholic News Archive.
 The paper includes a brief history of the organization and introduces the Portal and the Catholic Newspapers Program. Highlights include innovations in deep indexing and discovery through finding aids across aggregated content, digital content, text mining applications, and links to additional Catholic digital resources.

Ireland’s economic crisis and austerity: the response of the Irish Catholic Bishops

ABSTRACTThe Irish Roman Catholic Church has been a dominant institution in Irish society for generations but this dominance has declined in recent decades due to modernisation and secularisation. Since the mid-1990s, the Church has been rocked by scandals of clerical and religious sex abuse of children, which has had a negative impact on its moral standing in Irish society. As a result of the economic crash in 2008, a programme of severe austerity was introduced by the Irish government. In this article, the response of the Irish Catholic Bishops to the recession and austerity measures is assessed through the analysis of their public statements which are available through the news archive of the Irish Bishops’ Conference. The findings show that the Bishops did criticise the socio-economic policies of the Irish government but this was limited due to a range of institutional barriers.

Enhanced news sentiment analysis using deep learning methods

We explore the predictive power of historical news sentiments based on financial market performance to forecast financial news sentiments. We define news sentiments based on stock price returns averaged over one minute right after a news article has been released. If the stock price exhibits positive (negative) return, we classify the news article released just prior to the observed stock return as positive (negative). We use Wikipedia and Gigaword five corpus articles from 2014 and we apply the global vectors for word representation method to this corpus to create word vectors to use as inputs into the deep learning TensorFlow network. We analyze high-frequency (intraday) Thompson Reuters News Archive as well as the high-frequency price tick history of the Dow Jones Industrial Average (DJIA 30) Index individual stocks for the period between 1/1/2003 and 12/30/2013. We apply a combination of deep learning methodologies of recurrent neural network with long short-term memory units to train the Thompson Reuters News Archive Data from 2003 to 2012, and we test the forecasting power of our method on 2013 News Archive data. We find that the forecasting accuracy of our methodology improves when we switch from random selection of positive and negative news to selecting the news with highest positive scores as positive news and news with highest negative scores as negative news to create our training data set.

'A world of competing sorrows': A mixed methods analysis of media reports of children with cancer abandoning conventional treatment.

BackgroundWe aimed to provide health practitioners greater insight into the public perception of traditional and complementary medicine (T&CM) use. Our objectives were to identify news media reports of children abandoning conventional treatment for traditional and complementary medicine, analyze the thematic content of these news articles and estimate the tonality portrayed.MethodsLexisNexis and Factiva were searched for terms related to cancer, children and T&CM. Inclusion criteria were children less than 18 years, in curative phase of treatment who attempted to abandon conventional therapy for any traditional and complementary medicine use. A secondary search was performed in LexisNexis, Factiva and Google News Archive with the names of children in identified cases. Qualitative analysis of news media reports was completed using a grounded theory approach. Quantitative analysis of article sentiment was performed using a linear support vector machine.ResultsSeventeen cases occurring between 2002 and 2016 were included. Five main themes were identified: treatment as torture, power imbalances, rights of parents, evidence versus beliefs and the rights of Indigenous Peoples. Sentiment analysis revealed an overall negative tone, as demonstrated by 73% of the articles.InterpretationA better understanding of factors that lead to abandonment of conventional therapy for traditional and complementary medicine as portrayed in the news media may help healthcare providers prevent the occurrence of these cases.

Saving Data Journalism

Important works of data journalism are disappearing from the web because they are too technologically complex to be captured or archived by libraries or web archiving technologies. Research based on journalism depends on the existence of news archives. For the benefit of future scholars, it is imperative that libraries and newsrooms solve this problem. This research contends that dynamic web archiving of data journalism will require a new, emulation-based approach to capturing these works. This new approach in turn necessitates new web archiving tools and workflows to enable collaborative collection of the projects, because unlike in print-based archiving, the process will depend on detailed technical information sharing among stakeholders.Toward this end, this article summarizes the results of a questionnaire that described the most common frameworks, database technologies, and programming languages used to build 76 complex works of data journalism published between 2008 and 2017, as well the ways these works are being maintained and stored. This information can inform the development of emulation-based archiving tools to capture and preserve these stories using methods that would fit within the workflow of news organizations. This research is a first step toward devising an automated solution for long-term preservation of data journalism projects.

Timely assessment of disaster and emergency response networks in the aftermath of superstorm Sandy, 2012

PurposeThe purpose of this paper is to elaborate pros and cons of two coding methods: the rapid network assessment (RNA) and the manual content analysis (MCA). In particular, it focuses on the applicability of a new rapid data extraction and utilization method, which can contribute to the timely coordination of disaster and emergency response operations.Design/methodology/approachUtilizing the data set of textual information on the Superstorm Sandy response in 2012, retrieved from the LexisNexis Academic news archive, the two coding methods, MCA and RNA, are subjected to social network analysis.FindingsThe analysis results indicate a significant level of similarity between the data collected using these two methods. The findings indicate that the RNA method could be effectively used to extract megabytes of electronic data, characterize the emerging disaster response network and suggest timely policy implications for managers and practitioners during actual emergency response operations and coordination processes.Originality/valueConsidering the growing needs for the timely assessment of real-time disaster response systems and the emerging doubts regarding the effectiveness of the RNA method, this study contributes to uncovering the potential of the RNA method to extract relevant data from the megabytes of digitally available information. Also this research illustrates the applicability of MCA for assessing real-time disaster response networks by comparing network analysis results from data sets built by both the RNA and the MCA.

Choosing the perfect shot - The loaded narrative of imagery in online news coverage of vaccines.

Images in health communication have been shown to affect perspectives and attitudes towards health issues including vaccination. We seek to quantify the frequency of images used in online news coverage of vaccines that may convey varying sentiments about vaccination. To capture a breadth of vaccine-related news coverage, including international sources, we searched the following terms in Google News Archives: “autism and vaccine”, “flu and vaccine”, and “measles and Disneyland”. We developed a coding tool that classified images as negative (eg, screaming child), positive (eg, happy child), neutral (eg, vaccine vial), or irrelevant (eg, picture of journalist). All images were coded independently by two researchers and discussed for consensus. We analyzed 734 images. Of the images which featured vaccines and/or a medical encounter (322), 28% had negative features and 30% had positive features. The remaining 137 images (43%) were neutral. There was no statistically significant difference between proportions of negative and positive imagery for each pair of search terms, which may be a reflection of random image selection. Ultimately, nearly one in eight images included in vaccine-related news coverage contains negative features which may be selected without careful consideration of the potential negative impact on public health initiatives regarding vaccination.

Research and implementation of event extraction from twitter using LDA and scoring function

With the fast growth of social media, interest is increasing in detecting popular events from tweets. Event extraction is a work which identifies events from tweets or database of tweets. Each and every day, hundreds of megabytes of current stories are being added into the news archives of the major news agencies, containing much important and interesting news. Aim of this event extraction strategy is to extract and retrieve major life events from twitter data. Example of events extraction include seminar presentation, Job opening, Admission in Top universities, new technology etc. The role of this extraction is to collect major life events in the form of retrievable entries that include structured data about major life event name, location and time. Most of previous research on event extraction was mainly on textual level extraction such as News, medical systems, text summarization, whereas less work has been done on event extraction from noisy text such as tweets. For instance, tweets are short and self-contained which make them lack useful information. The target of this research is to develop algorithm and methodology that extract and efficiently conclude major life events extracted from social media.

Market impact analysis via deep learned architectures

How to deeply process market data sources and build systems to process accurate market impact analysis is an attractive problem. In this paper, we build up a system that exploits deep learning architecture to improve feature representations, and adopt state-of-the-art supervised learning algorithm—extreme learning machine—to predict market impacts. We empirically evaluate the performance of the system by comparing different configurations of representation learning and classification algorithms, and conduct experiments on the intraday tick-by-tick price data and corresponding commercial news archives of stocks in Hong Kong Stock Exchange. From the results, we find that in order to make system achieve good performance, both the representation learning and the classification algorithm play important roles, and comparing with various benchmark configurations of the system, deep learned feature representation together with extreme learning machine can give the highest market impact prediction accuracy.

The relevance of flood hazards and impacts in Turkey: What can be learned from different disaster loss databases?

Turkey has been severely affected by many natural hazards, in particular earthquakes and floods. Especially over the last two decades, these natural hazards have caused enormous human and economic damage. Although there is a large body of literature on earthquake hazards and risks in Turkey, comparatively little is known about flood hazards and risks. Therefore, this study aims to investigate the severity of flooding in comparison with other natural hazards in Turkey and to analyse the flood patterns by providing an overview of the temporal and spatial distribution of flood losses. These will act as a metric for the societal and economic impacts of flood hazards in Turkey. For this purpose, Turkey Disaster Database (TABB) was used for the years 1960–2014. As input for more detailed event analyses, the most severe flood events in Turkey for the same time interval will also be retrieved. Sufficiency of the TABB database to achieve the main aim of the study in terms of data quality and accuracy was also discussed. The TABB database was analysed and reviewed through comparison, mainly with the Emergency Events Database (EM-DAT), the Global Active Archive of Large Flood Events—Dartmouth Flood Observatory database, news archives and the scientific literature, with a focus on listing the most severe flood event. The comparative review of these data sources reveals big mismatches in the flood data, i.e. the reported number of events, number of affected people and economic loss all differ dramatically. Owing to the fact that the TABB is the only disaster loss database for Turkey, it is important to explore the reasons for the mismatches between TABB and the other sources with regard to aspects of accuracy and data quality. Therefore, biases and fallacies in the TABB loss data are also discussed. The comparative TABB database analyses show that large mismatches between global and national databases can occur. Current global and national databases for monitoring losses from national hazards suffer from a number of limitations, which in turn could lead to misinterpretations of the loss data. Since loss data collection is gaining more and more attention, e.g. in the Sendai Framework for Disaster Risk Reduction 2015–2030, this study offers a framework for developing guidelines for the Turkey Disaster Database (TABB), implications on how to standardize national loss databases and implement across the other hazard events in Turkey.

Educating Journalism Students About News Archives: A Global Comparison With Special Focus on Spain and the United States

Journalists and news archivists are natural allies. Journalists require previously published reporting as context for their new stories. Archivists ensure that material is preserved for future retrieval. Local news archives serve as a cultural, legal, economic, and genealogical resource for their communities. Now, the archiving function in news organizations is relegated to information vendors with little input from journalists. Rarely are journalism and archiving coupled in programs that train future professionals. This article explores the current state of journalism and library science education globally and suggests ways to strengthen education in news archiving in these programs.

Multiple perpetrator rape in Ghana: offenders, victims and offence characteristics

ABSTRACTMultiple perpetrator rape (MPR) is criminalised in Ghana but there is a dearth of research and official statistics on the phenomenon. This study explores some of the key characteristics of MPR in Ghana as reported in the media. Keyword search of the news archives of 9 Ghanaian media outlets generated 57 cases of MPR reported from January 2000 through June 2016. Content analysis of the cases showed 61 all-female victims and 57 all-male perpetrator groups. The average victim age was 17.9 years and the modal perpetrator-group size was two. The majority of the victims knew at least one member of the perpetrator groups. The perpetrator groups approached their victims outdoors but raped them indoors, using violent techniques to compel compliance. Although the characteristics of MPR in Ghana, as observed in this study, are comparatively similar to those found in other African countries, further studies are recommended for a nuanced understanding of MPR in Ghana.

米国のテレビニュース資料アーカイブズ( 音楽・映像のドキュメンテーション)

米国のテレビニュース資料アーカイブズ( 音楽・映像のドキュメンテーション)

A Framework for Unpublishing Decisions

This article explores the conflict between traditional ethical news values and unpublishing requests, which have arisen as a result of the availability of digital news archives. In so doing, this article provides a framework for how news organizations can make unpublishing decisions by weighing the sensitivity of the information published against its news value.