Selected Publications

More publications

Lexical Semantic Change detection, i.e., the task of identifying words that change meaning over time, is a very active research area, …

This data collection contains the post-evaluation data for SemEval-2020 Task 1

This paper is an overview of the opportunities and challenges of using large-scale text mining to answer research questions that stem …

State-of-the-art models of lexical semantic change detection suffer from noise stemming from vector space alignment. We have …

State-of-the-art models of lexical semantic change detection suffer from noise stemming from vector space alignment. We have …

In this paper, we discuss a data-intensive research methodology for the digital humanities. We highlight the differences and …

This article is a survey of recent computational techniques to tackle lexical semantic change, in particular we focus on diachronic …

Detecting word sense changes can be of great interest in the field of digital humanities. Thus far, most investigations and automatic …

We present a method for detecting word sense changes by utilizing automatically induced word senses. Our method works on the level of …

The concept of culturomics was born out of the availability of massive amounts of textual data and the interest to make sense of …

In this paper we describe the creation of a gold standard for the sentiment annotation of Swedish terms as a first step towards the …

High impact events, political changes and new technologies are reflected in our language and lead to constant evolution of terms, …

Recent Publications

More Publications

Lexical Semantic Change detection, i.e., the task of identifying words that change meaning over time, is a very active research area, …

This data collection contains the post-evaluation data for SemEval-2020 Task 1

Aspect-Based Sentiment Analysis constitutes a more fine-grained alternative to traditional sentiment analysis at sentence level. In …

This paper is an overview of the opportunities and challenges of using large-scale text mining to answer research questions that stem …

Swedish Test Data for SemEval 2020 Task 1

State-of-the-art models of lexical semantic change detection suffer from noise stemming from vector space alignment. We have …

State-of-the-art models of lexical semantic change detection suffer from noise stemming from vector space alignment. We have …

In this paper, we discuss a data-intensive research methodology for the digital humanities. We highlight the differences and …

The KubHist Corpus is a massive corpus of Swedish historical newspapers, digitized by the Royal Swedish library, and available through …

We process and visualize Swedish parliamentary data using methods from statistics and machine learning, which allows us to obtain …

Recent & Upcoming Talks

A keynote on data science for DH and Literary studies, September 2020

A workshop on data science for DH and Literary studies, September 2020

In this workshop, we wish to foster discussions between Natural Language Processing researchers, (digital) humanists, and historical …

A presentation of LSC in Helsinki, 2019

Mitt anförande om den oändliga texten, fördelar och nackdelar med data science för textforskning.

A Keynote for EDH2018 in Tartu.

Projects

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SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection

Computational detection of lexical and semantic change from diachronic texts.

NEER

An Unsupervised Method for Named Entity Evolution Recognition

Towards Computational Lexical Semantic Change Detection

Computational detection of lexical and semantic change from diachronic texts.

Culturomics

Towards a Knowledge-based Culturomics.

ARCOMEM

From Collect-All Archives to Community Memories – Leveraging the Wisdom of the Crowds for Intelligent Preservation

LiWA

Developing the next generation web archive technologies - Living Web Archives

Teaching

I have the following teaching experiences

2020

Lecturer, HUM3101 Statistik för humanister (PhD course in statistics for humanties, together with Åsa Wengelin), Spring

2018

Lecturer, LV2190 Methods in Digital Humanities (part Methods for text mining and visualization), Spring

2017

Supervisor, Master thesis, Spring 2017
Lecturer, LT2304 Language Technology Resources, Autumn

2016

Supervisor, Master theses, Spring
Lecturer, LT2304 Language Technology Resources, Autumn

2011

Supervisor, Master thesis

2010

Supervisor, Master theses, 2010

2007

Matematisk statistik för K, (TMA072) 2007 formulas

Summer Course Mathematics (MVE800) 2007

Matematik TB (LMA162) 2007

Contact