This thesis deals with the task of identifying implicit citations between scientific publications. Apart from being useful knowledge on their own, the citations may be used as input to other problems such as determining an author’s sentiment towards a reference, or summarizing a paper based on what others have written about it. We extend two recently proposed methods, a Machine Learning classifier and an iterative Belief Propagation algorithm. Both are implemented and evaluated on a common pre-annotated dataset. Several changes to the algorithms are then presented, incorporating new sentence features, different semantic text similarity measures as well as combining the methods into a single classifier. Our main finding is that the introduction of new sentence features yield significantly improved F-scores for both approaches. / Detta examensarbete behandlar frågan om att hitta implicita citeringar mellan vetenskapliga publikationer. Förutom att vara intressanta på egen hand kan dessa citeringar användas inom andra problem, såsom att bedöma en författares inställning till en referens eller att sammanfatta en rapport utifrån hur den har blivit citerad av andra. Vi utgår från två nyliga metoder, en maskininlärningsbaserad klassificerare och en iterativ algoritm baserad på en grafmodell. Dessa implementeras och utvärderas på en gemensam förannoterad datamängd. Ett antal förändringar till algoritmerna presenteras i form av nya särdrag hos meningarna (eng. sentence features), olika semantiska textlikhetsmått och ett sätt att kombinera de två metoderna. Arbetets huvudsakliga resultat är att de nya meningssärdragen leder till anmärkningsvärt förbättrade F-värden för de båda metoderna.

Citations allow researchers to define relationships across articles and develop arguments by building on the work of others. This study explores citation of theory symbols in Instructional Design and Technology (IDT) academic articles. The term theory symbol is used to define a concept that, after its original publication, is subsequently incorporated by later writers through citation. Exploring the citation history of the seminal publications makes it possible to trace theory symbol use over time and thus to trace its dissemination in the field. A typology of theory symbol use in IDT academic publication is developed through a citation context analysis (CCA) of a sample of articles published in Educational Technology Research and Development (ETRD) and its predecessor journals (1953–2012) which incorporate theory symbols through citation. This analysis contributes to an understanding of how theory has shaped IDT disciplinary knowledge and augments discourse analysis and bibliometrics by examining the context in which theory is incorporated into academic publication. / Ph. D. / This study explores the citation of theory symbols in Instructional Design and Technology (IDT) academic articles. A <i>theory symbol</i> is a concept that is included in a publication deemed to be foundational to a theory’s creation or development and subsequently incorporated by later writers through citation. Exploring the relationships between these cited and citing documents, with specific attention to the content of prior work passed from one to the other, makes it possible to trace the dissemination of theory symbols in the field and develop a typology of theory symbol use in IDT academic publication. This process is called citation context analysis (CCA) (Ritchie, 2008). A sample of articles published in <i>Educational Technology Research and Development</i> (ETRD) and its predecessor journals (1953–2012) serves as the foundation of the study. This analysis contributes to an understanding of how theory has shaped IDT disciplinary knowledge by examining the context in which theory is incorporated into academic publication. As Baskerville and Dulipovici (2006) argue, it is valuable to understand the application of theory because theory is used to support research arguments, methodology and in turn the development of other theories.