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Information Behaviour & Political Refugees

Titel: Miss-information amongst refugees

Miss-information, half-truths and fake news have received considerable attention in the media in recent times. Most of the research attention in this space has focused on social-media and how rumors and untruths are spread. However, false information can be spread in many ways.

Taking the refugee population as a case study, the aim of this project is to determine whether there are commonly held beliefs that are formed within refugee communities in Germany that are not true and understand how are these formed.

Kontaktperson: PD Dr. David Elsweiler

Titel: Information sharing / withholding amongst refugees - a study in the mould of Elfrede Chatman

Elfrede Chatman can be considered as one of the most influential information scientists. Her work studied information poverty and in particular she used ethnographical methods to understand the information landscape and behaviour of particular social groups, including university janitors, elderly women in care homes and the homeless. This project would continue her work to understand another underprivileged demographic - political refugees in Germany.

Skills and interests: qualitative research

Kontaktperson: PD Dr. David Elsweiler

Titel: Information seeking strategies of refugees

The refugee crisis has brought increasing numbers of refugees to Germany. When they arrive here they are encountered with many hurdles. How do things work? Where I can I stay? How long can I stay? Where can I get support? Cultural differences mean that the answers are often puzzling and all of this happens in a foreign language. This project will attempt to discover how refugees attempt to find answers to these kinds of questions. More specifically it will try to answer What kinds of information needs refugees have? What information resources do they have, which ones do they use hand how? What problems do they encounter?

Kontaktperson: PD Dr. David Elsweiler

Information Behaviour & Healthy Lifestyles

Titel: Analysing Trends in Online Supermarket Data

Government health initiatives often try to encourage home cooking as a means to promote healthier diets [1,3]. Nevertheless past studies have shown that common sources of cooking inspiration, such as recipes published by celebrity chefs tend to be unhealthier in many ways [2]. These kinds of studies are typically based on very small hand picked samples. In Howard's work a sample of recipes from celebrity cookbooks with a small sample of ready meals from UK supermarkets. While such studies are insightful, they do not show the full picture.

This project would involve crawling data from the website http://www.mysupermarket.co.uk/ to determine a more accurate and complete dataset from which to investigate the healthiness of ready meals. When the dataset has been created data mining approaches can be employed to answer a number of questions, which previous studies have not yet been able to answer. These include:

  • How healthy are ready meals?
  • Does this vary across stores?
  • Is there a relationship between price and healthiness?
  • Is there a relationship between popularity and healthiness?


Department of health. change4life marketing strategy. 2009. available athttp://www.nhs.uk/Change4Life/supporter-resources/downloads/Change4Life_Marketing%20Strategy_April09.pdf. last accessed on20.6.2016.

Howard, Simon, Jean Adams, and Martin White. "Nutritional content of supermarket ready meals and recipes by television chefs in the United Kingdom: cross sectional study." BMJ 345 (2012).

Usda.cookmoreoftenathome.2011.availableathttp://www.choosemyplate.gov/weight-management-calories/weight-management/better-choices/cook-home.html. last accessed on20.6.2016

Kontaktperson: PD Dr. David Elsweiler

Titel: Studying how online recipes are used in practice

Our recent work has demonstrated that users of online food portals generally prefer less healthy meals and their choices can be influenced by several factors including presentation, algorithms and personal preferences. That being said, just because online recipes are interacted with online does not mean that they are actually prepared and consumed by users. This project will investigate how online recipes are actually used in practice and more specifically, attempt to answer the following research questions:

  • When and why do people use online recipes? (for special occasions? to try something new? because they cannot cook without them?)
  • How are they used? Do people tend to follow the ingredients and instructions exactly or are they just used as inspiration?
  • When do users deviate and why?
  • In which ways and to what extent does the finished product vary from what is described in the recipe?

The results are important not only because they help us understand people’s behaviour, but also to help us estimate to what extent interactions with online recipes can be seen as a proxy for eating a meal with particular nutritional content.

Potential approaches: diary study, interview, observation.

Kontaktperson: PD Dr. David Elsweiler

Food ordering system for a sports club

Although participating in sport is typically associated with a healthy lifestyle, many of the community sports clubs in Germany provide particularly unhealthy food to the members. This project would involve developing an online food ordering system allowing members to order their food in advance. Not only would this make life easier for both the members and the restaurant, it would also provide a platform to understand food recommendations and potential behavioural change.

Kontaktperson: PD Dr. David Elsweiler

Website / Search engine to communicate and explore the geographical trends in health statistics and how this relates to the online food recipes with which people in those regions interact.

This project will involve indexing online recipes to make them searchable and at the same time visualising the trends found in recent publication.
Here is an example of such a site as means of inspiration.

Kontaktperson: PD Dr. David Elsweiler

Social Media Analysis

Titel: Analysing Following and Unfollowing Dynamics in Social Media Click-Through Data

Eine wesentliche Eigenschaft von Social Media Anwendungen ist der Aufbau eines sozialen Netzwerkes. Um den Nutzer bei der Suche nach potentiellen Accounts zu unterstützten, werden in der Forschung einige Möglichkeiten erörtert, die auf inhalts- oder auch netzwerkbasierten Verfahren basieren. Motivation und Auslöser, die erklären, wie Nutzer im Nutzungsalltag an das Problem herangehen und ihr soziales Netzwerk erweitern oder andere Nutzer aus ihrem sozialen Netzwerk entfernen, sind wenig bekannt.

Anhand eines Click-Through-Datensatzes von 44 Nutzern, der in einem Zeitraum von 5 Monaten erhoben wurde, soll analysiert werden, wie häufig neue Nutzer „gefolgt“ oder „entfolgt“ werden, nach welchen Anlässen dies der Fall ist und wie Nutzer dabei vorgehen.

[1] Haewoon Kwak, Hyunwoo Chun, and Sue Moon. 2011. Fragile online relationship: a first look at unfollow dynamics in twitter. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '11). ACM, New York, NY, USA, 1091-1100. DOI=http://dx.doi.org/10.1145/1978942.1979104

[2] Seth A. Myers and Jure Leskovec. 2014. The bursty dynamics of the Twitter information network. In Proceedings of the 23rd international conference on World wide web (WWW '14). ACM, New York, NY, USA, 913-924. DOI=http://dx.doi.org/10.1145/2566486.2568043

Kontaktpersonen: PD Dr. David Elsweiler

Titel: Detecting social media posts on controversial topics

The content posted on social-media is extremely diverse, ranging from posts documenting personal activities to opinions and statements of facts. Some of these facts are mundane and undisputed whereas others are extremely controversial. The aim of this project is to identify controversial tweets posted by German politicians. The student will develop and test automatic methods of detection using a large collection of tweets collected by elected politicians in Germany, which is being collected as part of an i:imsk collaboration.

This will involve some technical and programming skills as well as knowledge of statistics.

Kontaktperson: PD Dr. David Elsweiler

Titel: Studying images posted by politicians on Twitter

There are increasing numbers of studies investigating the social-media behaviour of politicians. These have applied both qualitative and quantitative approaches, demonstrating that politicians have diverse aims and behaviours, but in doing so exhibit many key cultural phenomena known from cultural studies. Many of the Tweets politicians post contain images. The aim of this project is to understand what kinds of images are posted, in which situations and why they might want to do this. The student will be provided with access to a large collection of tweets collected by elected politicians in Germany, which is being collected as part of an i:imsk collaboration.

Kontaktperson: PD Dr. David Elsweiler

Persuasive Computing

Titel: Games with sensors to encourage children in their movement and increase coordination skills.

According to the WHO, 41 million children under the age of 5 were overweight or obese in 2014 (WHO2014). However, obesity is preventable with a combination of healthy diet and adequate physical exercise. The aim of this project is to devise and develop interactive games for children to play, which will encourage them to be more active.

This project will require and interest in / and knowledge of programming and embedded systems (via raspberry pi).

Kontaktperson: PD Dr. David Elsweiler

Recommender Systems

Titel: Colour-based Food recommender

The colourfulness of food plays a key role in food choice by influencing taste thresholds, sweetness perception, food preference, pleasantness, and acceptability [1]. A large body of research has shown that changing the hue or intensity of the colour of food items can exert a sometimes dramatic impact on the expectations and subsequent experiences of consumers [2]. There is also evidence suggesting meals with broad range of colours tend to more healthy.

While it makes sense that the image associated with a recipe will be important in determining how it is perceived and rated, in the recommender systems community no research to date has investigated this in detail. Using large datasets collected via popular Internet food portals (allrecipes.com and kochbar.de), this project will study the relationship between the colourfulness of food images and perception of the food and will investigate the feasibility of using colour information to provide recommendations. Potential research questions include:

Does the colour profile of a recipe correlate with the healthiness of the recipe? Does the colour profile of a recipe correlate with the popularity of the recipe? Is it possible to predict user recipe ratings based on the colour profiles of previously liked recipes?

[1] Clydesdale, Fergus M. "Color as a factor in food choice." Critical Reviews in Food Science & Nutrition 33.1 (1993): 83-101. http://www.ncbi.nlm.nih.gov/pubmed/8424857

[2] Spence, Charles. "On the psychological impact of food colour." Flavour 4.1 (2015): https://flavourjournal.biomedcentral.com/articles/10.1186/s13411-015-0031-3

[3] http://blog.revolutionanalytics.com/2015/03/color-extraction-with-r.html

Kontaktperson: PD Dr. David Elsweiler

Titel: FoodChoice: an eye-tracking study

A lot of research has been performed in fields such as nutritional science and psychology to understand and model how people choose the food they eat. From this research we know choosing food is a complex, multi-faceted process, influenced by biological, personal and socio-economical factors [1]. Yet for the majority of people, aspects of taste and sensory appeal seem to be the drivers for decisions, followed by health concerns, nutritional value, and price [3], meaning that the decisions can be modelled using relatively simple heuristics [4].

In this project the aim is to use eye-tracking to confirm whether this holds in the context of choosing dishes on online food portals. We wish to understand, which information people use to base their decision of which recipe to try and determine whether particular features (e.g. title, image, nutritional information boxes) influence the decision of which food is chosen. Such an understanding could lead to the possibility of changing the information shown in order to influence the recipe chosen to promote health.

Methodological inspiration for the study can be found in [2].

[1] Bellisle F. The determinants of food choice. EUFIC Review. 2005;17(April):1–8.

[2] Fernquist, Jennifer, and Ed H. Chi. "Perception and understanding of social annotations in web search." Proceedings of the 22nd international conference on World Wide Web. ACM, 2013.

[3] Rozin P, Zellner D. The role of pavlovian conditioning in the acquisition of foodlikes and dislikesa. Annals of the New York Academy of Sciences.1985;443(1):189–202

[4] Scheibehenne B, Miesler L, Todd PM. Fast and frugal food choices: Uncoveringindividual decision heuristics. Appetite. 2007;49(3):578–589

Kontaktperson: PD Dr. David Elsweiler

Fußgängernavigation & Landmarkenforschung

Titel: Auswertung der URWalking-Logdaten

Unsere URWalking-Webapp speichert seit einigen Monaten alle Anfragen samt Geokoordinaten etc. in einer Datenbanktabelle. Die Tabelle ist ziemlich gewachsen und dementsprechend unübersichtlich.

Um unsere Navigation besser an die Bedürfnisse der Nutzer anpassen zu können, wäre nun beispielsweise interessant:

  • Welche Nutzer fragen Routen ab (sind das nur Lehrstuhlmitarbeiter oder auch Studenten oder andere Mitarbeiter)?
  • Welche Ziele werden abgefragt und wie können wir diese Daten nutzen, um unser System sinnvoll zu erweitern?
  • Welche Probleme treten bei der Start-/Zieleingabe auf?
  • Wie interagieren Nutzer mit dem System?

Nötig wären Grundkenntnisse in Datenbanken (PostgreSQL) und Erfahrung mit einer beliebigen Programmiersprache.

Kontaktpersonen: PD Dr. David Elsweiler

WLAN Heatmaps (in Kooperation mit dem Rechenzentrum)

Für die URWalking-Android-App soll eine Funktion entwickelt werden, die Nutzern anzeigt, wo sie die beste WLAN-Qualität haben.

Kontaktperson: Prof. Dr. Bernd Ludwig

Bewegungslogging über WLAN

Für die URWalking-Android-App soll eine Funktion entwickelt werden, die über das Speichern von empfangenen WLAN-Signalen aufzeichnet, welche Hotspots Nutzer passieren. Daraus sollen präferierte Routen abgeleitet werden.

Kontaktperson: Prof. Dr. Bernd Ludwig

Ihre Meinung ist uns wichtig! Bewertung von Routensegmenten im Außenbereich


Die konkreten Erfahrungen einer Person während der Navigation sind prägend für zukünftige Navigationserlebnisse. Es ist daher sinnvoll, diese Erfahrungen systematisch, flächendeckend zu sammeln. Dabei muss vor allem die Kleinteiligkeit dieser Erfahrungen in den Blick genommen werden. Schlechte Erfahrungen auf Routenabschnitten beeinflussen unter Umständen das Empfinden bezüglich der gesamten Route.
Ziel der Arbeit

Auf Grundlage des Datenmodells, das von der Geoinformatik-Gruppe der Universität Augsburg bereitgestellt wird, soll ein web-basiertes UI entwickelt werden.
Die Applikation soll folgende Aspekte abbilden:
1) Selektieren/Markieren von Routenabschnitten in Outdoor-Umgebungen
2) Fragebogen-gestützte Befragung von Personen aus der Anwendung heraus
3) Übertragung der Daten im vorgegebenen Datenmodell an einen Webserver
Mit dieser Applikation sollen anschließend Daten erhoben und ausgewertet werden.

Kontaktperson: Prof. Dr. Bernd Ludwig

Weitere Themen:

  • Vorhersage von Landmarken
  • Generierung kontextabhängiger Navigationsinstruktionen
  • Sprach-Interface für die URWalking-Android-App mit Chatfunktion
  • Crowdsourcing von Landmarken
  • Bewertung von Landmarken als games with a purpose

Kontaktperson: Prof. Dr. Bernd Ludwig

Natural Language Processing

Titel: CookBERT - Kochen mit BERT

Die Vorstellung des bekannten BERT-Papers von Devlin et al. hat im Jahr 2019 eine kleine Revolution im NLP-Bereich ausgelöst. Denn im Vergleich zu anderen Deep Learning-Modellen kann BERT mit Hilfe seines Self-Attention-Mechanismus Wortbedeutungen und Kontext besser erfassen. Dadurch konnten bis dato aktuelle State-of-the-Art-Modelle, etwa im Bereich des Question Answering und der Sentiment Analyse, bei weitem übertroffen werden.

Während der Fokus zu Beginn hauptsächlich auf englischen BERT-Modellen lag, gibt es diese mittlerweile auch für die französische (CamemBERT) und deutsche (GermanBERT) Sprache. Solche Modelle sind meistens auf der Wikipedia und Nachrichtenartikeln trainiert, d.h. sie bilden das Vokabular und den Kontext in dieser Textform entsprechend gut ab. Möchte man BERT für bestimmte Domänen, wie z.B. das Kochen, nutzen, fehlt Information über domänenspezifisches Vokabular und deren (kontextueller) Verwendung, was sich möglicherweise negativ auf die Performance auswirkt.

Im Rahmen einer Abschlussarbeit soll für die Kochdomäne ein deutsches (und englisches) BERT-Modell erstellt werden. Darüber hinaus soll überprüft werden, ob dieses im Vergleich zu anderen BERT-Modellen zu einer Verbesserung bei Klassifikationsaufgaben im Kochbereich, wie der Vorhersage von Informationsbedürfnissen während des Kochens, führt oder nicht.


  •     Interesse an NLP- und Machine Learning-Problemen
  •     Gute Python-Kenntnisse
  •     Idealerweise bereits erste Erfahrungen mit Keras

Kontaktpersonen: Udo Kruschwitz, David Elsweiler und/oder Alexander Frummet.

Kooperation mit Industriepartnern

Aktuell werden in diesem Bereich keine Abschlussarbeiten angeboten.

  1. Fakultät für Sprach-, Literatur- und Kulturwissenschaften
  2. Institut für Information und Medien, Sprache und Kultur (I:IMSK)