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This paper shows how new technologies open up significant research and development opportunities for the PR industry. It reviews public relations evaluation methodologies that can progress from evaluating media coverage of small numbers of “messages” to the development of systems for analysis of both objective and subjective texts. Applications include internal, external, research and media content. The paper looks to the next generation of analysis using International Standards Organisation (SGML) and web‐based technologies such as NewsML and XTM (both XML derivatives) in the processes of content and analysis, particularly as it can be applied to themes and topic analysis. The paper makes public for the first time the concept of corporate superthemes.

Recent archiving and curatorial practices took advantage of the advancement in digital technologies, creating immersive and interactive experiences to emphasize the plurality of memory materials, encourage personalized sense-making and extract, manage and share the ever-growing surrounding knowledge. Audiovisual (AV) content, with its growing importance and popularity, is less explored on that end than texts and images. This paper examines the trend of datafication in AV archives and answers the critical question, “What to extract from AV materials and why?”.

This study roots in a comprehensive state-of-the-art review of digital methods and curatorial practices in AV archives. The thinking model for mapping AV archive data to purposes is based on pre-existing models for understanding multimedia content and metadata standards.

The thinking model connects AV content descriptors (data perspective) and purposes (curatorial perspective) and provides a theoretical map of how information extracted from AV archives should be fused and embedded for memory institutions. The model is constructed by looking into the three broad dimensions of audiovisual content – archival, affective and aesthetic, social and historical.

This paper contributes uniquely to the intersection of computational archives, audiovisual content and public sense-making experiences. It provides updates and insights to work towards datafied AV archives and cope with the increasing needs in the sense-making end using AV archives.

The resurgence of right-wing parties and movements in almost all Member States of the European Union seems to indicate an escalating crisis not only of the European political project, but also of the societal fabric across Europe. In order to better comprehend its origins, it is important to understand how the identification of citizens with the EU is being shaped and challenged by attitudes including rising nationalism, Euroscepticism and anti-immigration feelings. While the focus during the current political crises has been overwhelmingly on statements and policies made by politicians, parties and institutions, this chapter instead studies the perceptions of the ‘common people’ and how they construct their identities within the European discourse, thus closing an important research gap.

This contribution is based on empirical data gathered during a large-scale project called Restorative Circles for Citizens in Europe, financed by the Europe for Citizens programme of the European Commission. Between January and June 2017, individuals from different walks of life came together in Trebnitz and Berlin to talk about ‘their’ Europe. Originally envisaged as an opportunity for dialogue between Eurosceptics and pro-Europeans, it soon revealed that there are many nuances in these attitudes. The presence of members and sympathisers of populist and right-wing movements and parties in the meetings changed the communication dynamics, and offered a unique opportunity to observe how (bottom-up) identity is constructed and what impact it has. This contribution analyses the extensive collected data.

A marketing‐centric view of the connected enterprise implies that qualitative information in its systems and general document structures share a marketing‐based vocabulary – we propose that this should be founded on POSIT. As any system needs to be accessed and understood by people, the basis of its construction and navigation principles should be transparent even though many component processes will be automated. Based on the use of natural language, a user‐defined glossary stems from a selection of primitives and relationships between them. Semantic mapping employing the reciprocal text‐to‐graphical capability of EXPRESS and EXPRESS G is outlined. The significance of XML and related developments is introduced in the context of qualitative information search and extraction from documents. Consensual language also aids connectivity of intranets and extranets to the Internet.

The purpose of this paper is to describe a new ontological content‐based filtering method for ranking the relevance of items for readers of news items, and its evaluation. The method has been implemented in ePaper, a personalised electronic newspaper prototype system. The method utilises a hierarchical ontology of news; it considers common and related concepts appearing in a user's profile on the one hand, and in a news item's profile on the other hand, and measures the “hierarchical distances” between these concepts. On that basis it computes the similarity between item and user profiles and rank‐orders the news items according to their relevance to each user.

The paper evaluates the performance of the filtering method in an experimental setting. Each participant read news items obtained from an electronic newspaper and rated their relevance. Independently, the filtering method is applied to the same items and generated, for each participant, a list of news items ranked according to relevance.

The results of the evaluations revealed that the filtering algorithm, which takes into consideration hierarchically related concepts, yielded significantly better results than a filtering method that takes only common concepts into consideration. The paper determined a best set of values (weights) of the hierarchical similarity parameters. It also found out that the quality of filtering improves as the number of items used for implicit updates of the profile increases, and that even with implicitly updated profiles, it is better to start with user‐defined profiles.

The proposed content‐based filtering method can be used for filtering not only news items but items from any domain, and not only with a three‐level hierarchical ontology but any‐level ontology, in any language.