Measuring academic influence: Not all citations are equal

The importance of a research article is routinely measured by counting how many times it has been cited. However, treating all citations with equal weight ignores the wide variety of functions that citations perform. We want to automatically identify the subset of references in a bibliography that have a central academic influence on the citing paper. For this purpose, we examine the effectiveness of a variety of features for determining the academic influence of a citation. By asking authors to identify the key references in their own work, we created a data set in which citations were labeled according to their academic influence. Using automatic feature selection with supervised machine learning, we found a model for predicting academic influence that achieves good performance on this data set using only four features. The best features, among those we evaluated, were those based on the number of times a reference is mentioned in the body of a citing paper. The performance of these features inspired us to design an influence-primed h-index (the hip-index). Unlike the conventional h-index, it weights citations by how many times a reference is mentioned. According to our experiments, the hip-index is a better indicator of researcher performance than the conventional h-index

Harmonizing the Metadata Among Diverse Climate Change Datasets

One of the critical problems in the curation of research data is the harmonization of its internal metadata schemata. The value of harmonizing such data is well illustrated by the Berkeley Earth project, which successfully integrated into one metadata schema the raw climate datasets from a wide variety geographical sources and time periods (250 years). Doing this enabled climate scientists to calculate a more accurate estimate of the recent changes in Earth’s average land surface temperatures and to ascertain the extent to which climate change is anthropogenic. This paper surveys some of the approaches that have been taken to the integration of data schemata in general and examines some of the specific metadata features of the source surface temperature datasets that were harmonized by Berkeley Earth. The conclusion drawn from this analysis is that the original source data and the Berkeley Earth common format provides a promising training set on which to apply machine learning methods for replicating the human data integration process. This paper describes research in progress on a domain-independent approach to the metadata harmonization problem that could be applied to other fields of study and be incorporated into a data portal to enhance the discoverability and reuse of data from a broad range of data sources

Connecting with Youth at Risk: Indigenous Organizations Use of Facebook

A qualitative study in which we conducted four interviews with two communication managers and two youth program managers of three indigenous organizations with offices in Ottawa, the data generated from the interviews were coded based on factors identified through thematic analysis. Indigenous organizations use Facebook for two main reasons. The first reason is to promote the work of these organizations to the public and for them, in turn to listen to the public’s opinions about news related to indigenous peoples’ wellbeing. Secondly, Facebook is also used to engage urban indigenous youth at risk with indigenous organizations that provide social programs and outreach. Indigenous organizations use Facebook because many urban indigenous youth in Ottawa are using Facebook and it is the fastest way to connect with them when they are or feel at risk

The Complexity of Automated Reasoning

This thesis explores the relative complexity of proofs produced by the automatic theorem proving procedures of analytic tableaux, linear resolution, the connection method, tree resolution and the Davis-Putnam procedure. It is shown that tree resolution simulates the improved tableau procedure and that SL-resolution and the connection method are equivalent to restrictions of the improved tableau method. The theorem by Tseitin that the Davis-Putnam Procedure cannot be simulated by tree resolution is given an explicit and simplified proof. The hard examples for tree resolution are contradictions constructed from simple Tseitin graphs. iii Acknowledgements I would like to thank Steven Thomason, Marvin Belzer, David Goodman and William Older for their comments on early drafts of my thesis. I am very grateful to John Bell, James Brown, Hector Levesque, and John Slater for serving on my committee and also to William Seager for his equally interesting comments and his continual encouragemen..