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Historical newspaper collections provide a wealth of information about the past. Although the digitization of these collections significantly improves their accessibility, a large portion of digitized historical newspaper collections, such as those of KBR, the Royal Library of Belgium, are not yet searchable at article-level. However, recent developments in AI-based research methods, such as document layout analysis, have the potential for further enriching the metadata to improve the searchability of these historical newspaper collections. This paper aims to discuss the aforementioned issue.

In this paper, the authors explore how existing computer vision and machine learning approaches can be used to improve access to digitized historical newspapers. To do this, the authors propose a workflow, using computer vision and machine learning approaches to (1) provide article-level access to digitized historical newspaper collections using document layout analysis, (2) extract specific types of articles (e.g. feuilletons – literary supplements from Le Peuple from 1938), (3) conduct image similarity analysis using (un)supervised classification methods and (4) perform named entity recognition (NER) to link the extracted information to open data.

The results show that the proposed workflow improves the accessibility and searchability of digitized historical newspapers, and also contributes to the building of corpora for digital humanities research. The AI-based methods enable automatic extraction of feuilletons, clustering of similar images and dynamic linking of related articles.

The proposed workflow enables automatic extraction of articles, including detection of a specific type of article, such as a feuilleton or literary supplement. This is particularly valuable for humanities researchers as it improves the searchability of these collections and enables corpora to be built around specific themes. Article-level access to, and improved searchability of, KBR's digitized newspapers are demonstrated through the online tool (https://tw06v072.ugent.be/kbr/).

The purpose of this paper is to reconstruct the marketing history of medical marijuana cigarettes in the past three decades of Austria-Hungary.

This paper constructs an analytical narrative based on information scattered in historical periodicals.

Towards the end of Habsburg rule, two Ljubljana-based pharmacists, the Trnkóczy brothers, managed to establish themselves as monopolistic suppliers of pre-rolled medical marijuana cigarettes for the entire Austrian part of the dual monarchy. Garnering the support of the regional Carniolan Government, Julius von Trnkóczy successfully argued his wares were not affected by the prohibition passed against imported French medicinal cigarettes. This happened despite medical opposition, suggesting that Trnkóczys could only operate this business because of their elevated social status. In the past decade of the 19th century, Ubald von Trnkóczy took advantage of newly loosened regulation to obtain an official permit by the royal-imperial government in Vienna. This was followed, in late 1909, by an advertising campaign covering mass media throughout the empire. This was enabled, amongst others, by a cutting down on medicinal claims. Their declining price is further indication that the cigarettes were mass marketed, especially as their core ingredient, cannabis, underwent price inflation.

Because of its later illegality, the research subject was for a long time considered embarrassing, leading to an absence of retrievable documents. Missing archival sources are thus a major limitation, but one which can be overcome by the concurrent reading of historical periodicals – ranging from mass-market newspapers to specialist journals and legal texts. This paper has implications for 21st-century challenges in the marketing of newly legalized medical marijuana.

This paper discusses the marketing history of cannabis, a drug rarely discussed in historical literature outside its medical and regulatory context, and reconstructs previously forgotten case histories.

This chapter explores how data-driven methods such as Artificial Intelligence pose real concerns for individual privacy. The current paradigm of collecting data from those using online applications and services is reinforced by significant potential profits that the private sector stands to realize by delivering a broad range of services to users faster and more conveniently. Terms of use and privacy agreements are a common source of confusion, and are written in a way that dulls their impact and dopes most into automatically accepting a certain level of risk in exchange for convenience and “free” access. Third parties, including the government, gain access to these data in numerous ways. If the erosion of individual protections of privacy and the potential dangers this poses to our autonomy and democratic ideals were not alarming enough, the digital surrogate product of “you” that is created from this paradigm might one day freely share thoughts, buying habits, and your pattern of life with whoever owns these data. We use an ethical framework to assess key factors in these issues and discuss some of the dilemmas posed by Artificial Intelligence methods, the current norm of sharing one's data, and what can be done to remind individuals to value privacy. Will our digital surrogate one day need protections too?