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Presenting Tiered Recommendations in Social Activity Streams

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Presenting Tiered Recommendations in Social Activity Streams PRESENTING TIERED RECOMMENDATIONS IN SOCIAL ACTIVITY STREAMS A Thesis Submitted to the College of Graduate Studies and Research In Partial Fulfillment of the Requirements For the Degree of Master of Science In the Department of Computer Science University of Saskatchewan Saskatoon By WESLEY WALDNER Copyright Wesley Waldner, September, 2015. All Rights Reserved. PERMISSION TO USE In presenting this thesis in partial fulfilment of the requirements for a Postgraduate degree from the University of Saskatchewan, I agree that the Libraries of this University may make it freely available for inspection. I further agree that permission for copying of this thesis in any manner, in whole or in part, for scholarly purposes may be granted by the professor or professors who supervised my thesis work or, in their absence, by the Head of the Department or the Dean of the College in which my thesis work was done. It is understood that any copying or publication or use of this thesis or parts thereof for financial gain shall not be allowed without my written permission. It is also understood that due recognition shall be given to me and to the University of Saskatchewan in any scholarly use which may be made of any material in my thesis. Requests for permission to copy or to make other use of material in this thesis in whole or part should be addressed to: Head of the Department of Computer Science 176 Thorvaldson Building 110 Science Place University of Saskatchewan Saskatoon, Saskatchewan Canada S7N 5C9 i ABSTRACT Modern social networking sites offer node-centralized streams that display recent updates from the other nodes in one's network. While such social activity streams are convenient features that help alleviate information overload, they can often become overwhelming themselves, especially high-throughput streams like Twitter’s home timelines. In these cases, recommender systems can help guide users toward the content they will find most important or interesting. However, current efforts to manipulate social activity streams involve hiding updates predicted to be less engaging or reordering them to place new or more engaging content first. These modifications can lead to decreased trust in the system and an inability to consume each update in its chronological context. Instead, I propose a three-tiered approach to displaying recommendations in social activity streams that hides nothing and preserves original context by highlighting updates predicted to be most important and de-emphasizing updates predicted to be least important. This presentation design allows users easily to consume different levels of recommended items chronologically, is able to persuade users to agree with its positive recommendations more than 25% more often than the baseline, and shows no significant loss of perceived accuracy or trust when compared with a filtered stream, possibly even performing better when extreme recommendation errors are intentionally introduced. Numerous directions for future research follow from this work that can shed light on how users react to different recommendation presentation designs and explain how study of an emphasis-based approach might help improve the state of the art. ii ACKNOWLEDGMENTS I first must acknowledge the irreplaceable contribution of my graduate supervisor, Dr. Julita Vassileva. With her guidance and through our regular discussions about the field of social computing in general, I was able to search for unturned stones while exploring my interests in this area of research. I would not have made it to this point without the freedom to study something that was meaningful to me. I would also like to thank her for seeing something in me while I was still an undergraduate student and for giving me this opportunity that I would not have otherwise considered. Thanks go out to the other members of my committee—Dr. Winfried Grassmann, Dr. Regan Mandryk, and Dr. Chris Zhang—for their valuable input, corrections, and particularly for making sure that I kept the big picture in mind as I completed my studies and wrote this manuscript. Finally, I need to acknowledge the love and support of my family and of my wife, Jennie, in particular. Thank you for keeping me focused on the goal, for your encouragement, and for always knowing that I would make it to the end. iii CONTENTS PERMISSION TO USE ................................................................................................................. i ABSTRACT ................................................................................................................................... ii ACKNOWLEDGMENTS ........................................................................................................... iii CONTENTS.................................................................................................................................. iv LIST OF TABLES ....................................................................................................................... vi LIST OF FIGURES .................................................................................................................... vii INTRODUCTION......................................................................................................................... 1 1.1 Social Activity Streams .................................................................................................... 2 1.2 Research Questions .......................................................................................................... 7 LITERATURE REVIEW ............................................................................................................ 8 2.1 Information Overload ....................................................................................................... 8 2.2 Recommender Systems .................................................................................................. 10 2.2.1 Types of Recommendations .................................................................................... 10 2.2.2 Types of Recommenders......................................................................................... 11 2.3 Evaluating Recommender Systems ................................................................................ 13 2.3.1 Objective Metrics .................................................................................................... 13 2.3.2 Explanations ............................................................................................................ 15 2.4 Trust and Persuasiveness ................................................................................................ 16 2.5 Information Visualization .............................................................................................. 17 2.6 Social Recommendation ................................................................................................. 18 2.7 Summary ........................................................................................................................ 23 TIERS OF EMPHASIS IN TWITTER TIMELINES ............................................................. 25 3.1 Proposed Approach ........................................................................................................ 25 3.1.1 Design ..................................................................................................................... 25 3.2 One-Dimensional Stream Pilot Study ............................................................................ 27 3.2.1 Goals ....................................................................................................................... 27 3.2.2 Recommender System ............................................................................................ 28 3.2.3 Implementation ....................................................................................................... 30 3.2.4 Procedure ................................................................................................................ 31 3.2.5 Results ..................................................................................................................... 32 3.2.6 Discussion ............................................................................................................... 34 iv 3.3 Two-Dimensional Stream Pilot Study............................................................................ 35 3.3.1 Design ..................................................................................................................... 36 3.3.2 Implementation ....................................................................................................... 38 3.3.3 Goals ....................................................................................................................... 39 3.3.4 Procedure ................................................................................................................ 40 3.3.5 Results ..................................................................................................................... 41 3.3.6 Discussion ............................................................................................................... 45 3.3.7 Conclusions ............................................................................................................. 46 THE PERSUASIVENESS OF PURE EMPHASIS ................................................................. 47 4.1 Design............................................................................................................................
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