Semantic Variation in Online Communities of Practice

We introduce a framework for quantifying semantic variation of common words in Communities of Practice and in sets of topic-related communities. We show that while some meaning shifts are shared across related communities, others are community-specific, and therefore independent from the discussed topic. We propose such findings as evidence in favour of sociolinguistic theories of socially-driven semantic variation. Results are evaluated using an independent language modelling task. Furthermore, we investigate extralinguistic features and show that factors such as prominence and dissemination of words are related to semantic variation.Comment: 13 pages, Proceedings of the 12th International Conference on Computational Semantics (IWCS 2017

Zapotec Language Activism And Talking Dictionaries

Online dictionaries have become a key tool for some indigenous communities to promote and preserve their languages, often in collaboration with linguists. They can provide a pathway for crossing the digital divide and for establishing a first-ever presence on the internet. Many questions around digital lexicography have been explored, although primarily in relation to large and well-resourced languages. Lexical projects on small and under-resourced languages can provide an opportunity to examine these questions from a different perspective and to raise new questions (Mosel, 2011). In this paper, linguists, technical experts, and Zapotec language activists, who have worked together in Mexico and the United States to create a multimedia platform to showcase and preserve lexical, cultural, and environmental knowledge, share their experience and insight in creating trilingual online Talking Dictionaries in several Zapotec languages. These dictionaries sit opposite from big data mining and illustrate the value of dictionary projects based on small corpora, including having the flexibility to make design decisions to maximize community impact and elevate the status of marginalized languages

The discourse deictics ^ and <-- in a World of Warcraft community

In the written English variety used in a community of World of Warcraft players, two iconic lexical items created from symbols have undergone semantic change. The words analyzed are ^ and <--, which have shifted from iconic deictic items used for discourse reference to non-iconic epistemic meanings. ^ shifted from a discourse deictic to an affirmative of a previous utterance, and <-- shifted to a self-identifying meaning similar to a pronoun. The existence and evolution of these lexical items are related to the medium in which they were created, as their meanings are associated with a visual-spatial environment created by textual chat in the virtual world. The different meanings of ^ and <-- currently exist in polysemy in the community, and the continuum of meanings are documented using data from natural language use spanning three years. A statistical analysis is performed on the data, and a diachronic change in meaning is found; furthermore, the observed change follows the path of semantic shift processes previously documented in spoken language. © 2012 Elsevier Ltd

Freedom and Restraint: Tags, Vocabularies and Ontologies

The benefit of metadata is widely recognized. However, the nature of that information and the method of production remains a topic of some debate. This division is most noticeable between those who believe in ’free tagging’, and those who prefer the more formal construction of an ontology to define both the vocabulary of the domain and the relationships between the concepts within it. Looking at the community surrounding online amateur authors and the descriptive metadata they have developed over the last thirty years we consider what we can learn from a mature but amateur tagging community. This paper considers how these two systems might be used together to add the easy usability of free tagging to ontology descriptions and the conceptual richness of ontologies to free tags

Semantic modelling of user interests based on cross-folksonomy analysis

The continued increase in Web usage, in particular participation in folksonomies, reveals a trend towards a more dynamic and interactive Web where individuals can organise and share resources. Tagging has emerged as the de-facto standard for the organisation of such resources, providing a versatile and reactive knowledge management mechanism that users find easy to use and understand. It is common nowadays for users to have multiple profiles in various folksonomies, thus distributing their tagging activities. In this paper, we present a method for the automatic consolidation of user profiles across two popular social networking sites, and subsequent semantic modelling of their interests utilising Wikipedia as a multi-domain model. We evaluate how much can be learned from such sites, and in which domains the knowledge acquired is focussed. Results show that far richer interest profiles can be generated for users when multiple tag-clouds are combine

Evolutionary Subject Tagging in the Humanities; Supporting Discovery and Examination in Digital Cultural Landscapes

In this paper, the authors attempt to identify problematic issues for subject tagging in the humanities, particularly those associated with information objects in digital formats. In the third major section, the authors identify a number of assumptions that lie behind the current practice of subject classification that we think should be challenged. We move then to propose features of classification systems that could increase their effectiveness. These emerged as recurrent themes in many of the conversations with scholars, consultants, and colleagues. Finally, we suggest next steps that we believe will help scholars and librarians develop better subject classification systems to support research in the humanities.NEH Office of Digital Humanities: Digital Humanities Start-Up Grant (HD-51166-10

Towards improved performance and interoperability in distributed and physical union catalogues

Purpose of this paper: This paper details research undertaken to determine the key differences in the performance of certain centralised (physical) and distributed (virtual) bibliographic catalogue services, and to suggest strategies for improving interoperability and performance in, and between, physical and virtual models. Design/methodology/approach: Methodically defined searches of a centralised catalogue service and selected distributed catalogues were conducted using the Z39.50 information retrieval protocol, allowing search types to be semantically defined. The methodology also entailed the use of two workshops comprising systems librarians and cataloguers to inform suggested strategies for improving performance and interoperability within both environments. Findings: Technical interoperability was permitted easily between centralised and distributed models, however the various individual configurations permitted only limited semantic interoperability. Significant prescription in cataloguing and indexing guidelines, greater participation in the Program for Collaborative Cataloging (PCC), consideration of future 'FRBR' migration, and greater disclosure to end users are some of the suggested strategies to improve performance and semantic interoperability. Practical implications: This paper informs the LIS research community and union catalogue administrators, but also has numerous practical implications for those establishing distributed systems based on Z39.50 and SRW, as well as those establishing centralised systems. What is original/value of the paper?: The paper moves the discussion of Z39.50 based systems away from anecdotal evidence and provides recommendations based on testing and is intimately informed by the UK cataloguing and systems librarian community

Enriching videos with light semantics

This paper describes an ongoing prototypical framework to annotate and retrieve web videos with light semantics. The proposed framework reuses many existing vocabularies along with a video model. The knowledge is captured from three different information spaces (media content, context, document). We also describe ways to extract the semantic content descriptions from the existing usergenerated content using multiple approaches of linguistic processing and Named Entity Recognition, which are later identified with DBpedia resources to establish meanings for the tags. Finally, the implemented prototype is described with multiple search interfaces and retrieval processes. Evaluation on semantic enrichment shows a considerable (50% of videos) improvement in content description