Technologies: Rhetoric Analytics

In The New Ethos, we develop Rhetoric Analytics, i.e., a sense-making technology that provides insights into communication strategies used in large-scale discourse. It is founded upon data analytics, i.e., a wide-spread (cf. Business Intelligence, Media Analysis), science-enabled range of tools, techniques and processes used to convert raw data into insights, to analyse such data in order to make conclusions about information, to interpret them in a meaningful way and to extract knowledge. As a result, we are able to reveal statistical patterns, trends and tendencies of the variety of devices and strategies in rhetoric of the digital society.   The modular architecture of this technology allows us to develop each module of analytics independently and to add more and more modules that increase robustness in analysing variety of rhetorical and linguistic uses of language in the digital communication.   Below, you will find the description of the currently available modules of Rhetoric Analytics. At the very bottom, you will find the descriptions of corpora on which Rhetoric Analytics run.

LEPAn

Logos-Ethos-Pathos Analytics is the foundational tool in the Rhetoric Analytics technology, as it allows us to inspect the use of key strategies of logos, ethos and pathos in the rhetoric of the digital society. It enables the analyst to understand not only a single rhetorical device, but also to inspect similarities and differences between these three types of rhetorical behaviour.

LEPAn-v01. This is the initial version of the tool that allows the analysis of logos, ethos and pathos, as well as comparison between them in online discourse: (1) Reddit discussions on COVID-19 vaccination, PolarIs1; and (2) Reddit reactions to the US 2016 presidential debates, PolarIs5.

DynRephAn

Dynamics of Rephrase Analytics is the second foundational tool in Rhetoric Analytics, as it allows us to analyse the transformations of the use of rhetorical devices as a result of rephrasing information, i.e. to analyse them as they change when speakers rephrase what they say. The special role of DynRephAn consists in treating an argument relation of rephrase as a process of how a debate is evolving, how rhetorical devices are changed and manipulated by speakers. This means that we are able to inspect not only results of rhetorical or linguistic use of language, e.g., by comparing the frequencies of using logos vs ethos, but we are also able to trace how speakers were strategically influencing the character of the discussion, e.g., by shifting from using pure logos to using logos loaded with ethos.

DynRephAn-v01. This is the initial version of the tool that allows the analysis of ethos and sentiment in rephrase in social media, traditional media and face-to-face discussions in the following corpora: (1) Reddit discussions on COVID-19 vaccination, PolarIs1; (2) Reddit reactions to the US 2016 presidential debates, PolarIs5; (3) televised presidential debates in the US from 2016, USElections; and (4) UK parliamentary debates from the period of Margaret Thatcher as a prime minister, Hansard. It allows qualitative analysis of merged corpora or comparative study of each single corpus with dynamics of ethos or sentiment counts presented in piecharts, barcharts, wordclouds and tables.

DynRephAn-v02.  This is the extended version that allows more complex analysis of single corpus and comparative examinations of selected corpora. New options allow part of speech analysis, ranking of most frequent n-gram (up to 4-grams), parts of speech ranking, lexemes ranking and synonym group ranking as well as parts of speech combinations rankings.

MArgAn

Moral Argument Analytics is a tool in Rhetoric Analytics that allows us to investigate the use of moral values in argumentation. Morals serve as a core of what we believe and how we see the world. This is why a tool, which enables the identification and understanding of whether people appeal to dignity or loyalty, benevolence or justice, authority or equality, provides a deep insight into what truly drives a discussion and argumentation.

MArgAn-v01. This is the initial version of the tool that allows the automatic detection of moral foundations (defined according to the Moral Foundations Theory, Haidt and Joseph 2004) in large-scale datasets of dialogical arguments, and the statistical summaries and visual representations of moral foundations patterns in argumentation.

OLAn

OLAn is our tool that allows us to analyse the use of offensive language and to identify patterns and trends in its use. This rhetorical strategy is important, as it overlaps with hate speech and polarisation.

OLAn-v01. The initial version of OLAn is a social media analysis technology developed to understand the use of offensive language in social media discourse, i.e., in Twitter discussions during the 2021 United Nations Climate Change Conference. More specifically, it allows us to analyse and visualise patterns in offensive reactions to public figures across their social roles and popularity in polarised discourse online.

  • Available at: https://olan-v01.streamlit.app/, developed by He Zhang
  • User manual can be downloaded here: OLAn-v01 user manual
  • Please read and cite this paper, if you are using OLAn-v01 tool:
    — M. Kulik, K. Budzynska, H. Zhang, M-A. Paquin, B. Konat (2025) Offensive Language in Reactions to Public Figures in Polarised Discourse Online, Journal of Language Aggression and Conflict, John Benjamins Publishing Company. DOI 10.1075/jlac.00136.kul

Other tools

More information will be published soon on other tools developed in the Laboratory of The New Ethos. Papers that introduce them are currently in review, so we are not able to reveal their names and descriptions now.

Corpora

ETHOS SUPPORTS AND ATTACKS. The Thatcher’s Ethos in Hansard corpus was constructed by taking a random subsample of Hansard according to the following rubric: select the first two House of Commons debates over 700 words in length from the day closest to the date(s) at the midpoint(s) of the largest uninterrupted date range(s) (initially the midpoint in the range 4th May 1979 and 22nd November 1990 – viz., 11th February 1985; then at the midpoints between 4th May 1979 and 11th February 1985, and between 11th February 1985 and 22nd November 1990, etc.). This avoids bias for annotators and yielded 60 transcripts, the data in each of which was then cleaned such that any titles and section markers were removed to leave only the speakers, organisations or other entities and the statements they made. The transcripts were then split evenly to give a training set and a testing set. The training set formed the training data for the sentiment polarity classifier and was used as the basis for developing domain specific rules for recognising ethotic sentiment expressions.

Ethos support. Ethos support should be identified when: (a) the statement makes explicit mentions of a person, organisation or other entity (excluding groups and assemblages) except when this is reported speech; and (b) it takes the form of supporting a person’s credibility or looking to put them in a positive frame through character supports or supports of work; and (c) a support to a person’s own ethos should not be analysed as this is deemed to be a fallacy. Ethos attack. Ethos attack should be identified when: (a) the statement makes explicit mentions of a person, organisation or other entity (excluding groups and assemblages) except when this is reported speech; and (b) it takes the form of attacking a person’s credibility or looking to put them into a negative frame; or (c) it may take the form of trying to unbalance authority on a subject giving the attacker more of a right to talk about the subject.

Corpus Ethos-Hansard1 available at: https://corpora.aifdb.org/Hethos

Corpus Ethos-Hansard2 available at: https://corpora.aifdb.org/EthosHansard2

ETHOS TYPES: WISDOM, VIRTUE, GOODWILL. A 12% of the data was annotated by two annotators for the purpose of evaluation. Overall this gave Cohen’s kappa=0.42, a percentage agreement of 57\% and weighted $\kappa=0.63$. The kappa score is considered fair but the weighted kappa score shows room for improvement in the guidelines. To this extent a third annotator annotated a smaller 8% subset of the data to provide a pairwise agreement score. Comparing all three annotators gave Fleiss kappa = 0.51. A pairwise comparison of annotators one and three gave kappa = 0.63 and weighted kappa = 0.79. Comparing annotators two and three gave kappa = 0.51 and weighted kappa = 0.70.

Building upon the Aristotelian distinction between ethos types we proposed the annotation of ethos types using three main tags (Practical Wisdom, Moral Virtue and Goodwill) split into support and attack (Argument and Conflict) according to the following guidelines: Practical Wisdom: Argument From Practical Wisdom should be annotated when: (a) an entity is said to have sufficient knowledge for the purpose at hand; or (b) an entity can draw conclusions from this knowledge; or (c) an entity has practical experience; (d) an entity can draw conclusions from this experience. While Conflict From Practical Wisdom should be annotated when the opposite is true. Moral Virtue: Argument From Moral Virtue should be annotated when: (a) a statement refers to the character trait of an entity, when the entity shows positive morality, calmness, justness, selflessness, gracefulness, nobility, positive contributions, liberality, magnanimity or magnificence; or (b) when an entity provides the correct information. While Conflict From Moral Virtue should be annotated when the opposite is true. Goodwill: Argument From Goodwill should be annotated when: (a) a statement refers to an entity’s ability to show goodwill to others; or (b) an entity gives sound advice when it is know, ensuring the entity does not deceive while being inclusive; or (c) an entity aligns with an audience’s values, displaying self sacrifice. While Conflict From Goodwill should be annotated when the opposite is true.

LOGOS ACCORDING TO INFERENCE ANCHORING THEORY. In The New Ethos, logos is annotated according to Inference Anchoring Theory, IAT (Budzynska & Reed, 2010). This framework allows for the representation of argument, dialogical and illocutionary structures as well as interactions between the three of them. The first version of an IAT annotation scheme was developed by ARG-tech. We use two corpora that were created by this team: US2016tv and US2016reddit. Additionally, our team annotated two further corpora described below.

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