arXiv subjects

Alexander Henlein

Publications and source records attributed to Alexander Henlein.

4 recordsLinked to original sources

arXiv2024

You Shall Know a Tool by the Traces it Leaves: The Predictability of Sentiment Analysis Tools

If sentiment analysis tools were valid classifiers, one would expect them to provide comparable results for sentiment classification on different kinds of corpora and for different languages. In line with results of previous studies we show that sentiment analysis tools disagree on the same dataset. Going beyond previous studies we show that the sentiment tool used for sentiment annotation can even be predicted from its outcome, revealing an algorithmic bias of sentiment analysis. Based on Twitter, Wikipedia and different news corpora from the English, German and French languages, our classifiers separate sentiment tools with an averaged F1-score of 0.89 (for the English corpora). We therefore warn against taking sentiment annotations as face value and argue for the need of more and systematic NLP evaluation studies.

cs.CL↗

arXiv2024

The Spatial Semantics of Iconic Gesture

The current multimodal turn in linguistic theory leaves a crucial question unanswered: what is the meaning of iconic gestures, and how does it compose with speech meaning? We argue for a separation of linguistic and visual levels of meaning and introduce a spatial gesture semantics that closes this gap. Iconicity is differentiated into three aspects: Firstly, an interpretation of the form of a gesture in terms of a translation from kinematic gesture annotations into vector sequences (iconic model). Secondly, a truth-functional evaluation of the iconic model within spatially extended domains (embedding). Since a simple embedding is too strong, we identify a number of transformations that can be applied to iconic models, namely rotation, scaling, perspective fixation, and quotation of handshape. Thirdly, the linguistic description or classification of an iconic model (informational evaluation). Since the informational evaluation of an iconic gesture is a heuristic act, it needs a place in a semantic theory of visual communication. Informational evaluation lifts a gesture to a quasi-linguistic level that can interact with verbal content. This interaction is either vacuous, or regimented by usual lexicon-driven inferences discussed in dynamic semantic frameworks.

cs.CL↗

arXiv2022

What do Toothbrushes do in the Kitchen? How Transformers Think our World is Structured

Transformer-based models are now predominant in NLP. They outperform approaches based on static models in many respects. This success has in turn prompted research that reveals a number of biases in the language models generated by transformers. In this paper we utilize this research on biases to investigate to what extent transformer-based language models allow for extracting knowledge about object relations (X occurs in Y; X consists of Z; action A involves using X). To this end, we compare contextualized models with their static counterparts. We make this comparison dependent on the application of a number of similarity measures and classifiers. Our results are threefold: Firstly, we show that the models combined with the different similarity measures differ greatly in terms of the amount of knowledge they allow for extracting. Secondly, our results suggest that similarity measures perform much worse than classifier-based approaches. Thirdly, we show that, surprisingly, static models perform almost as well as contextualized models -- in some cases even better.

cs.CL↗

arXiv2020

The Frankfurt Latin Lexicon: From Morphological Expansion and Word Embeddings to SemioGraphs

In this article we present the Frankfurt Latin Lexicon (FLL), a lexical resource for Medieval Latin that is used both for the lemmatization of Latin texts and for the post-editing of lemmatizations. We describe recent advances in the development of lemmatizers and test them against the Capitularies corpus (comprising Frankish royal edicts, mid-6th to mid-9th century), a corpus created as a reference for processing Medieval Latin. We also consider the post-correction of lemmatizations using a limited crowdsourcing process aimed at continuous review and updating of the FLL. Starting from the texts resulting from this lemmatization process, we describe the extension of the FLL by means of word embeddings, whose interactive traversing by means of SemioGraphs completes the digital enhanced hermeneutic circle. In this way, the article argues for a more comprehensive understanding of lemmatization, encompassing classical machine learning as well as intellectual post-corrections and, in particular, human computation in the form of interpretation processes based on graph representations of the underlying lexical resources.

cs.CL↗