Hanna Schmück

I'm a Research Associate at the University of Glasgow working on the linguistic and data visualisation outputs of the OHOS Project. I am also a Doctoral Candidate, Research Assistant, and Associate Lecturer at Lancaster University. I greatly enjoy all things corpus linguistics, psycholinguistics, and data visualisation. The main aim of my work is to develop new, explainable methodologies and workflows so we can analyse (existing) linguistic data in new ways and further our understanding of language and the mind. Have a look at my research/projects, publications, learn more about me, and feel free to get in touch if you want to explore possible collaborations.

Current Role at the University of Glasgow

Research Associate - Information Studies, School of Humanities

The project I am working on, Our Heritage, Our Stories, is a Discovery Research Project funded by the Arts and Humanities Research Council, as part of the Towards a National Collection programme. It aims to to make community-generated digital content from a large number of different community archives more linkable, searchable, and to make it available alongside custodial resources like The National Archive. My main research area within this project is identifying how corpus linguists can benefit from the rich resources found in community archives and how language can be valued and appreciated as a heritage object. I have also created the visualisation outputs (named entity networks) for the project. These can be found here.

Projects and Experience at Lancaster University

Teaching - Undergraduate Modules
I have been teaching several modules at Lancaster University since 2020. Modules I have taught so far include LING228 (Child Language Acquisition), LING315 (Forensic Linguistics), and LING326 (Corpus Linguistics). I am currently teaching LING330 (Language, Cognition and Culture), LING324 (Cognitive Linguistics), and LING316 (Psycholinguistics).
Teaching - MOOC
I have been deputy lead / lead mentor for Lancaster's "Corpus Linguistics - Method, Analysis, Interpretation" online course for multiple years now. This course runs yearly, has multiple thousands of participants (at the time of writing a cumulative count of over 70,000) and I have been involved since 2020.

Teaching - Autumn School in Corpus Linguistics

Mentoring - Methods North West
I was working as a mentor for research students as part of a Methods NW project enabling interdisciplinary and interinstitutional research collaborations. My role involved advising the researcher in methodological matters with regards to corpus linguistics.
Mentoring - Coding Sessions
I am currently working as a mentor teaching other academics programming skills (R/Python). In this role, I design a curriculum around the researchers' individual project aims, set challenges, and cooperate with them to find efficient, robust, interpretable, and easily replicable solutions.
Teaching and Technical Assistance - Summer Schools in Corpus Linguistics
I have been helping with the Lancaster Summer Schools in Corpus Linguistics since 2020. This has involved both teaching Q&A sessions as well as helping with the technology behind the scenes (setting up and recording Teams live events, monitoring the chat, operating the presentations etc.).
Research Assistant Roles - BNC Assistant
I worked on preprocessing and data cleaning of the British National Corpus 2014 from 2020 to its publication in late 2021.
Research Assistant Roles - Data Processing
I worked on a syntactic coding project doing data cleaning and advanced preprocessing in 2022.
Research Assistant Roles - Manual Coding
I started working on a project investigating language testing data in the APTIS corpus, a corpus compiled in collaboration with the British Council. For this project, I carried out manual pragmatic coding.
Research Assistant Roles - Data Processing
I worked on L2 language proficiency test data, also from the APTIS corpus, mainly data processing, formatting and statistical analyses of epistemic markers.
Research Assistant Roles - LANA Corpus Processing
I currently work on the the Lancaster-Northern Arizona Corpus of American English (LANA) project in collaboration with colleagues at ASU.
Research Assistant Roles - Multimodal Corpora using CloudVision
I currently work on a multimodal newspaper corpus compilation project with Professor Paul Baker. My role entails writing custom Python scripts for collecting the corpus data from several UK newspaper websites, downloading and processing the images, interfacing with Google CloudVision and Vertex AI for image tagging, and designing the multimodal corpus. Alongside this, this project entails an extensive manual evaluation of using Vertex AI for mutimodal corpus analysis. I have further developed a small tool to display the images based on their tags to enable effective multimodal analyses.
Technical Assistant Roles - ECR Events
I did the recording and communication for the Quantitative Research Methods for Social Sciences for early career researchers event series. The videos of past sessions are available here.
Technical Assistant Roles - BNC launch event
I helped with the live stream and onsite organisation of the BNC launch event (over 1,200 participants) in 2021.
Technical Assistant Roles - CHIMED-3
I helped with the live stream and onsite organisation of the CHIMED-3 conference in 2023.
Volunteering - Postgraduate Liaison of the LAEL Society
I was the postgraduate liaision of the LAEL Society from 02/2020 to 06/2022.

Independent Projects and Experience

COMPILE Learning - Open Access Programming Skills Development
I coordinate the Lancaster branch of COMPILE and teach select pyhton and regex lectures.
Lone Wolf Networks

Conferences and Presentations

Please click on headings to see abstracts/videos.

CL2021 - 16.-20.07.2021, Limerick Ireland (online)

I presented findings from my PhD project at the International Conference for Corpus Linguistics.
A video of my talk can be accessed here:

UCREL - 03.06.2021, Lancaster University (online)

I gave a talk on "Traversing Language Structures: Creating, Exploring and Visualising Large Scale Linguistic Networks" as part of the UCREL seminar series.
Abstract: How does the language we are surrounded by differ from the language in our Mental Lexicon? We try to explore this question by developing new methods to display, analyse and compare large-scale linguistic networks using graph-theoretical parameters. The aim is to examine structural similarities and differences between a collocation network (based on the BNC2014 / BNC2014 Baby+(Brezina, 2019)) and a psycholinguistic network (based on cue-response pairs provided by over 90,000 participants for the SWOW-EN project (De Deyne et al., 2018)) in order to further our understanding of the relationship between language perception and language production. In addition to this, a new, dynamic visualisation of said networks furthermore allows for identifying "latent patterns" (Dong & Buckingham, 2018) in the data that would not have been observable when starting an analysis using pre-determined words of interest. In this presentation, the methodology and overarching justifications for the project will be presented alongside a demonstration of several custom network visualisations in Cytoscape (Shannon et al., 2003) and a case study exploring properties of the BNC2014 Baby+ and SWOW-EN.

A video of my talk can be accessed here:

'Annotations' Summer School / École thématique d’été « Annotations » - 30.05.-03.06.2022, Banyuls-sur-Mer

I gave a talk titled 'Lessons Learnt from Graphing Linguistic Connections' at the École thématique d’été « Annotations » in France. This conference/summer school was organised by GDR Lift/Sorbonne.

ICAME43 - 27.-30.07.2022, Cambridge, UK

I presented methodological findings from my PhD project at the 43rd Annual Conference of the International Computer Archive for Modern and Medieval English (ICAME)
My abstract can be found here (page 152).

In the wake of many 'new normals' in linguistics, new tools to explore linguistic data are steadily being proposed and implemented. This study aims to showcase one of these novel approaches: large scale linguistic network visualisations and how they can shed light on the interplay between language production and language perception. For the purpose of demonstrating strengths and limitations of this approach we carry out a case study on the basis of the following research questions: What is the collocational embedding of the word normal in spoken British English? What shape might the associative embedding of the word normal in native BrE speaker's mental lexicon take? In order to explore this, a multidisciplinary approach is taken that spans corpus linguistics, psycholinguistics and graph theory. The exact method employed to investigate word embeddings/context here is based on a custom-built python scripts used to pre- process and weight corpus data as well as word association data. First sentence-span tuples from the spoken BNC 2014 (Love et al, 2017) are extracted while retaining their directionality – an often underreported yet crucial property (Michelbacher et al., 2011; Gries; 2013, McConnell & Blumenthal-Dramé, 2019) – and the corresponding MI2 scores are calculated. Then the Small World of Words word association database (SWOW; De Deyne et al, 2019) is processed and filtered to only contain responses by British participants for comparability with the BNC. The obtained collocations (MI2 ≥ 10) and association pairs (Association weight ≥ 1) are fed to Cytoscape (Shannon et al., 2003) via py4cytoscape. The visual representations of the BNC and SWOW-UK networks surrounding the word normal (Figures 1 and 2) are created on the basis of an edge- weighted spring directed layout (Kamada & Kawai, 1989) which roughly maps MI2 scores and association weights onto the displayed distances between words. Lastly, a range of graph theoretical properties for both networks are extracted and interpreted. The results indicate that both the complete SWOW UK network and the complete Spoken BNC 2014 network exhibit small world properties (Watts & Strogatz, 1998). Qualitatively speaking, the collocations surrounding normal in the spoken BNC 2014 are generally sparser and the resulting subnetwork is denser than the one emerging from word associations. In the BNC, key topics surrounding the term are personal relationships and looks. These are organised around a strong network core composed of discourse markers and frequent verbs such as like, really, well etc. The word association dataset, however, looks markedly different and almost fractures into five distinct topic areas: antonyms of normality, society, health, abstract notions of normality, and discourse surrounding drugs. This suggests discrepancies between the mental association processes surrounding abstract terms such as normal and usage of such terms in everyday conversation. Lastly, further applications of this methodology are briefly remarked upon. These include optimising language pedagogy practices (Xiao & McEnery, 2006; Webb & Kagimoto, 2009) via assessing how central certain terms are to a learner's language network and exploring network cliques which is useful for lexicography (Gablasova et al., 2017; Simpson-Vlach & Ellis, 2010) and researching language change (Chen et al., 2018).

CL2023 - 03.-06.07.2023, Lancaster, UK

CL2023 talk
At CL2023 I presented two papers: Two approaches to collocation networks: GraphColl and LLN (with Vaclav Brezina) and Deconstructing Discourses – A network-based approach to analysing Lone Wolf Terrorism in British Newspapers (see Book of Abstracts).
I also helped organise and chair sessions.

Abstract (I): This paper compares two approaches to the creation and analysis of collocation networks: the GraphColl function currently available through #LancsBox and #LancsBox X (Brezina et al., 2020) and a Python and Cytoscape-based (Shannon et al., 2003) custom pipeline for visualisation and graph theoretical analysis of corpus-wide linguistic networks (LLN). Collocation networks are used to visualise discourse relationships, "aboutness" of a text or discourse, semantic relations (Pecina, 2010; Xiao & McEnery, 2006; Brezina, 2016; Baker, 2016; Brezina et al., 2015) as well as lexicogrammatical features (McEnery & Brezina, 2019). GraphColl is an accessible tool to view collocational relationships localised to a particular area of discourse; it allows selecting a particular set of search terms, association measure parameters, window spans and thresholds, and retains information on the type, lemma and POS level before plotting collocation networks. LLN, on the other hand, is the result of a methodological triangulation (Noble & Heale, 2019; Tucker & Ernestus, 2016) and integration synthesis (Wyatt, 2022) of concepts from corpus linguistics and graph theory. A core difference is that LLN yields graph theoretical parameters that describe all collocations found in the entire corpus thus producing much larger networks. It also incorporates a graph theoretical exploration e.g. in order to compare different corpora via their collocational density, the average distance between their collocates, etc. Beyond these global descriptions, LLN also allows for clustering to explore different 'layers of discourse'. This paper will provide an in-depth demonstration of how the collocation networks generated by the two tools differ. The case study will focus on the topic of substance abuse across discourses represented in the BNC2014 (Brezina et al., 2021; Love et al., 2017). The implications for corpus-based discourse analysis will be discussed.

Abstract (II). The aim of this paper is to showcase interdisciplinary novel approaches to collocation network analysis via a case study on lone wolf terrorism discourses in the British press using the Lone Wolf Corpus (LWC; Malone, 2020). Aboutness, special functions of words, and semantic relations are highly relevant when examining discursively complex topics such as lone wolf terrorism, and all of these features emerge from collocational profiles (Pecina, 2010; Xiao & McEnery, 2006; Brezina, 2016; Baker, 2016; Brezina et al., 2015). Extending this line of thought, an analysis of clusters containing heavily interrelated collocates can represent different layers of discourses contained in a corpus and thus constitute a valuable addition to the linguist's toolbox. The LWC contains just under 8.5 million words of British newspaper coverage on lone wolf terrorism and serves as the basis for discourse cluster generation. spaCy (Montani et al., 2022) is used for POS-tagging and lemmatising the texts, collocation scores for all sentence-level bigrams (CPN: 6a-LogLikelihood(50), sentence, C0-NC0; filtered to only contain nouns, lexical verbs, adverbs, and adjectives[1]) are then generated in Python. The graph theoretical visualisation and analysis of the remaining list of collocations is carried out via py4cytoscape (Shannon et. al, 2003). Lastly, clusters are extracted using MCODE (Bader & Hogue, 2003) and the Girvan-Newman fast greedy clustering algorithm (Girvan & Newman, 2002). Emerging clusters are visualised using edge weighted spring directed layouts (Kamada & Kawai, 1989). The results show that topically similar clusters (here: clusters containing temporal and special information related to terrorist attacks, names of terrorists and victims, weapons, and organisations) emerge across the different subsections of the LWC. The observed clusters present a first step towards more holistic insights into discursive patterns while moving away from an exclusively intuition-based starting point for linguistic analysis (Castro & Siew, 2020; Sinclair & Coulthard, 1975; Dong & Buckingham, 2018) .This underlines the notion that the application of graph theoretical methods to language data displays both theoretical and methodological potential (Vitevitch & Goldstein, 2014). [1] Here taken to represent the lexicalised end of the lexicogrammatical spectrum.

Edge Hill Corpus Research Group - 14.12.2023

Edge Hill talk 2023 Daniel Malone (Edge Hill) and I presented on 'A pack of lone wolves? Exploring the nexus between the lone-wolf terrorist, Al-Qaeda, and ISIS in the British Press' as part of the Edge Hill Corpus Research Group (see EHCRG website)

Abstract:
Following recent events in Belgium and Israel, the lone-wolf terrorist re-emerged in media reportage, with President Joe Biden and former GCHQ Director Sir David Omand expressing concerns over potential attacks in the USA and UK. Days later, Belgian Prime Minister Alexander De Croo described the neutralised Brussels shooter as “probably a lone wolf,” thus aiming to downplay the risk of subsequent incidents. Together, these instances exemplify that by shaping a “reality” (Entman, 2004), (in)security discourses can amplify or downplay a terrorist threat, in turn reflecting and/or influencing public perception and potentially guiding policy responses. Historically, the lone wolf has been associated with different movements, ranging from the propaganda of the deed in the 19th Century to the leaderless resistance of white-supremacist groups in the 1980s and 90s. More recently, it is within the domain of Islamist terrorism, often dominated by Al-Qaeda and ISIS, where the lone wolf has become increasingly associated, especially in the British press. In this joint presentation, we discuss the analytical approaches and results from our analysis of discourses surrounding the lone-wolf terrorist, al Qaeda, and ISIS in three diachronic sub-corpora of the Lone Wolf Corpus (Malone, 2020), a compilation of British Press articles from 2000 to 2019. In a unique methodological combination, we employed large-scale collocation networks and topical clustering to examine shifting discourses through collocational clusters, and applied a corpus-based critical discourse analysis to examine representations of the Al-Qaeda-ISIS nexus. Hanna introduces the methodology employed to generate topical clusters and discusses collocational changes and constants in emerging discourses surrounding the lone-wolf terrorist. The resulting patterns present a discursive shift from clusters related to causative factors (e.g., a mental health subcluster), towards the internationalisation and institutionalisation of lone-wolf terrorism, and finally to response management in the form of sentencing and punitive actions (e.g., a court proceedings/prison subcluster). Reporting on his corpus-based critical discourse analysis, Daniel presents the emergent representations surrounding co-occurrences of the node AL QAEDA with ISIS. These discourses were categorised into four modes of representation of presented relationship-types: Convergence, Association, Dissociation, and Divergence. These modes contributed to surrounding (in)security discourses that at times equate, promote and/or relegate different entities in a continual reshuffling of the threat hierarchy; a process termed here enmity reimagining.

Digital Humanities Forum - 08.02.2024, Lancaster University

DH Forum Presentation 2024 I presented parts of my ongoing work on network explorations of linguistic data in my talk titled "Mapping Meaning: Large Linguistic Networks in the Digital Humanities Landscape" with a focus on applicability in the wider DH space. See presentation here and visualisations here Spoken BNC & Academic BNC.

ICAME 45 - 18.06.- 22.06.2024, Vigo, Spain

ICAME presentations 2024 I have had two full papers accepted for ICAME 45 in Vigo. The first paper is a collaboration with Samuel Hollands (Sheffield University) titled Towards a Pipeline Approach to Corpus Compilation: Challenges and Solutions and the second paper is single-authored titled Graphing Registers - Exploring Register Differences via Collocational Networks in the BNC2014

Abstract (I):
Despite enormous financial and time investments in many modes of corpus compilation there is often a lack in consistency with regards to corpus processing, format, and structure (Demmen, 2020; Diemer et al., 2016, Reppen, 2022). Issues spanning domains and impacting comparability of spoken and written corpora (Lindquist & Levin, 2000) include irregular metadata formats, inconsistent data structures, varied transcription approaches amongst others. In the domain of speech corpora, we see additional issues such as methodologically unjustified variation in audio formats. This paper aims to explore ways in which both written and spoken corpus compilation can be streamlined and, as an example, which best practices can be employed for constructing eBook corpora. Recommendations relevant to both researchers working with spoken and written corpora are provided in order to highlight the importance of working towards a methodological conversion in these two domains.
Within this study we are proposing the Python Corpus Pipeline (PCPi) to streamline corpus compilation via programmatic blueprints for ideal corpus structures. This allows researchers to automatically format corpora into a regular schema and encourages conscious decisions regarding limitations which often occur as a result of the absence of clear guidelines in the corpus creation phase. Specific recommendations are made to address issues in the spoken corpus domain such as varied microphone setups, irreversible acoustic post-processing of recordings, and inconsistent use of audio filetypes. For example, low-bitrate MP3, whilst near universally accepted as a very effective form of signal compression, is designed to remove as much information from an audio signal as possible whilst trying to preserve the human perception of the signal from a psychoacoustic perspective (Watkinson, 2012: 169-227). Therefore, whilst to the human ear the signal may appear unaltered, the information loss caused by signal compression can pose challenges from the perspective of speech scientists such as speech analytics for emotion recognition (Campbell, 2002; Lotz, 2017).
In the written domain we provide a worked example from the currently ongoing compilation of the Lancaster-Northern Arizona Corpus of American English (LANA). Even straightforward tasks such as removing the front and backmatter pose significant problems when working with epub files that do not follow a rigorous standard. This is the case since long acknowledgements or reading samples run the risk of mimicking the style of the desired main body of the text and chapter breaks are not reliably marked. The issue of formatting inconsistencies almost always occurs when eBooks are sourced from multiple publishers. As for the fiction section of LANA only 664 out of 1325 books available (50.1%) contained explicit and reliable chapter breaks. This paper describes the subroutine of the PCPi framework. This splits individual files into paragraphs and checks their contents in several passes to classify them as belonging to the main body of the text or not using a window-based approach, resulting in 1133 (85.5%) salvageable eBooks.
By advocating for standardized practices and exemplifying its application in eBook corpus construction, this study contributes to the ongoing efforts aimed at fostering methodological coherence within the diverse landscape of corpus linguistics through the oculus of the PCPi framework.

Abstract (II):
One of the many ways in which register differences and linguistic nuances within different fields of discourse can be explored and compared is via collocations, here broadly defined as a commonly co-occurring group or set of words (Barnbrook et al., 2013; Stulpinaitė et al., 2016). Previous research shows that register can be used to partially predict collocations in American English (Berber Sardinha, 2017), and underscores the significance of investigating how linguistic patterns contribute to the distinctive characteristics of various registers. This paper aims to explore register differences in the BNC2014 (v2; Love et al, 2017; Brezina et al., 2021) through the lens of collocational clusters derived from subcorpus-wide collocation networks Acknowledging the often-conflicting definitions of register and genre, this study adopts Biber and Conrad's (2019) interchangeable use of these terms, employing subcorpora of the BNC2014 as proxies for registers. The questions raised in this paper are how well collocation networks can capture register variation, which registers in the BNC2014 are the most collocationally similar/dissimilar, and what unique collocational clusters emerge from each subcorpus. In order to address these, a multidisciplinary approach spanning corpus linguistics and graph theory is used to generate networks of all collocations within each of the 8 subcorpora of the BNC: Academic Language, E-Language, Fiction, Magazines, Newspapers, Written-To-Be-Spoken, Official Documents, and Spoken Language. Following a methodology akin to Karaminis et al. (2023), the collocations are required to lie above both a ΔPforward and logDice threshold to ensure robustness in terms of the forwards predictability and coherence of the collocations. The large linguistic networks (LLNs) generated on the basis of these subcorpora represent the collocational profiles, structure, and aboutness (Pecina, 2010; Xiao & McEnery, 2006; Brezina, 2016; Baker, 2016; Brezina et al., 2015) of the respective registers in the BNC2014. MCODE clustering (Bader & Hogue, 2003) is employed in order to identify the collocationally most closely-interconnected clusters unique to each register. ICAME presentations 2024 Employing this methodology serves two purposes: Firstly, it allows for a systematic and fully interpretable exploration of large-scale differences in collocational tendencies among different registers of modern British English, and, secondly, it showcases which new avenues for interpretation a novel approach to collocation visualisation can bring. On a broader scale, notable collocational convergence is observed, with the highest overlap occurring between Magazines and News (20.2%), Spoken and Written-to-be-Spoken (19.9%), and E-Language and Spoken (19.6%). Conversely, the lowest overlap is evident between Official Documents and Written-to-be-Spoken (2.0%), Academic Language and Written-to-be-Spoken (2.3%), and Fiction and Official Documents (3.2%). ICAME presentations 2024 Figures 1 and 2 show key clusters from the opposing domains of Official Documents and Written-To-Be-Spoken respectively. This novel multidisciplinary approach integrating corpus linguistics and graph theory with MCODE clustering presents a new way for systematically exploring register variation.
Figure 1: Subcluster containing collocates unique to Official Documents in the BNC2014.
Figure 2: Subcluster containing collocates unique to Written-To-Be-Spoken in the BNC2014.

Invited talks/ guest lectures

Corpus Linguistics and Collocation Networks - School of Foreign Languages at the University American College Skopje, North Macedonia
Research Management and Open Access via the OSF - COMPILE
Lessons learnt from teaching Python - PyData Lancaster, see presentation here
Mapping Meaning: Large Linguistic Networks in the Digital Humanities Landscape - DH Forum @ Lancaster University
Large Linguistic Networks: A case study on Lone-Wolf Terrorism in the British Press - University of Glasgow

Attended Conferences and Events (selection)

Brexit means Brexit? Ein Symposium - Akademie der Wissenschaften, Mainz - 03-07 December 2017
BAAL Corpus Linguistics Special Interest Group Annual Worskhop: Corpora, Discourse and Society - Lancaster - 13 November 2019
Advanced Language Processing Winter School - ALPS, 17-22 January 2021
Machine Learning for Humanists - N8 CIR June 2021
The International Corpus Linguistics Conference 2021 - 13-17 July 2021
École thématique d'été « Annotations » - 30 May - 03 June 2022
The 43rd Annual Conference of the International Computer Archive for Modern and Medieval English - Corpus Linguistics: A New Normal? 27-30 July 2022
CHIMED-3, 3rd International Conference on Historical Medical Discourse - London - 11-12 May 2023
CL2023, 12th International Corpus Linguistics Conference - Lancaster - 03-06 July 2023
The 45rd Annual Conference of the International Computer Archive for Modern and Medieval English - Corpus Linguistics: Interlocking Corpora and Register(s): Diversity and Innovation. 28-22 June 2024
UCREL NLP Summer School 2024 - 24-26 July 2024
Towards a National Collection Conference - 20-21 November 2024
BEYOND conference - 25-27 November 2024

Data visualisation of attended events (in-person and online during COVID)

Interests

When I'm not working I really enjoy crafting, painting, playing (video)games (particularly platformers), exploring the Lake District, throwing some darts, and listening to podcasts.
I won a Green Lancaster competition and since also enjoy cycling in and around Lancaster.

I am a Klaus Murmann Doctoral Fellow at Stiftung der deutschen Wirtschaft gGmbH (Foundation of German Business/ UK regional group) and a winner of the Geoffrey Leech Outstanding MA Student Award for my MA in Language and Linguistics.