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99
Adaptive interfaces and agents
, 2003
"... As its title suggests, this chapter covers a broad range of in-teractive systems. But they all have one idea in common: that it can be worthwhile for a system to learn something about each individual user and adapt its behavior to them in ..."
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Cited by 101 (10 self)
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As its title suggests, this chapter covers a broad range of in-teractive systems. But they all have one idea in common: that it can be worthwhile for a system to learn something about each individual user and adapt its behavior to them in
Do you know?: recommending people to invite into your social network
- In IUI ’09: Proceedings of the 13th international conference on Intelligent user interfaces
, 2009
"... In this paper we describe a novel UI and system for providing users with recommendations of people to invite into their explicit enterprise social network. The recommendations are based on aggregated information collected from various sources across the organization and are displayed in a widget, wh ..."
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Cited by 47 (11 self)
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In this paper we describe a novel UI and system for providing users with recommendations of people to invite into their explicit enterprise social network. The recommendations are based on aggregated information collected from various sources across the organization and are displayed in a widget, which is part of a popular enhanced employee directory. Recommended people are presented one by one, with detailed reasoning as for why they were recommended. Usage results are presented for a period of four months that indicate an extremely significant impact on the number of connections created in the system. Responses in the organization’s blogging system, a survey with over 200 participants, and a set of interviews we conducted shed more light on the way the widget is used and implications of the design choices made. ACM Classification
Searching for experts in the enterprise: combining text and social network analysis
- Proc. Group'07
, 2007
"... Employees depend on other people in the enterprise for rapid access to important information. But current systems for finding experts do not adequately address the social implications of finding and engaging strangers in conversation. This paper provides a user study of SmallBlue, a social-context-a ..."
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Cited by 39 (3 self)
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Employees depend on other people in the enterprise for rapid access to important information. But current systems for finding experts do not adequately address the social implications of finding and engaging strangers in conversation. This paper provides a user study of SmallBlue, a social-context-aware expertise search system that can be used to identify experts, see dynamic profile information and get information about the degrees of separation or social distance to the expert, before deciding whether and how to initiate contact. The system uses an innovative approach to privacy to infer content and dynamic social networks from email and chat logs. We describe usage of SmallBlue and discuss implications for the next generation of enterprise-wide systems for finding people. Categories and Subject Descriptors
Discovering Personal Gazetteers: An Interactive Clustering Approach
- In Proc. ACMGIS
, 2004
"... Personal gazetteers record individuals' most important places, such as home, work, grocery store, etc. Using personal gazetteers in location-aware applications o#ers additional functionality and improves the user experience. However, systems then need some way to acquire them. ..."
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Cited by 30 (6 self)
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Personal gazetteers record individuals' most important places, such as home, work, grocery store, etc. Using personal gazetteers in location-aware applications o#ers additional functionality and improves the user experience. However, systems then need some way to acquire them.
Making sense of strangers' expertise from signals in digital artifacts
- Proc. CHI '09
, 2009
"... Contemporary work increasingly involves interacting with strangers in technology-mediated environments. In this context, we come to rely on digital artifacts to infer characteristics of other people. This paper reports the results of a study conducted in a global company that used expertise search a ..."
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Cited by 23 (1 self)
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Contemporary work increasingly involves interacting with strangers in technology-mediated environments. In this context, we come to rely on digital artifacts to infer characteristics of other people. This paper reports the results of a study conducted in a global company that used expertise search as a vehicle for exploring how people interpret a range of information available in online profiles in evaluating whom to interact with for expertise. Using signaling theory as a conceptual framework, we describe how certain ‘signals ’ in various social software are hard to fake, and are thus more reliable indicators of expertise. Multi-level regression analysis revealed that participation in social software, social connection information, and selfdescribed expertise in the corporate directory were significantly helpful in the decision to contact someone for expertise. Qualitative analysis provided further insights regarding the interpretations people form of others’ expertise from digital artifacts. We conclude with suggestions on differentiating various types of information available within online profiles and implications for the design of expertise locator/recommender systems. Author Keywords Signaling, expertise search, social software, social networks
FriendSensing: Recommending Friends Using Mobile Phones
- In ACM RecSys
, 2009
"... Social-networking sites, such as Facebook, require members to manually find and confirm their friends. Finding friends is tedious for some and may be made less so by automating the process. We propose to do so by means of a framework that we call FriendSensing. Using short-range technologies (e.g., ..."
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Cited by 19 (1 self)
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Social-networking sites, such as Facebook, require members to manually find and confirm their friends. Finding friends is tedious for some and may be made less so by automating the process. We propose to do so by means of a framework that we call FriendSensing. Using short-range technologies (e.g., Bluetooth) on their mobile phones, social-networking users “sense ” and keep track of other phones in their proximity. Proximity records are then processed using a variety of algorithms that are based on social network theories of geographical proximity and of link prediction. This processing can be performed either on the social-networking website, after records have been uploaded, or locally on the user’s mobile phone, so that privacy-conscious individuals do not have to disclose their proximity data to the socialnetworking website. The result is a personalized and automatically generated list of people the user may know. We evaluate the extent to which FriendSensing helps users find people they know, and we do so against real mobility and social network data.
Same places, same things, same people? Mining user similarity on social media
- in Proc. CSCW, ser. CSCW ’10
"... In this work we examine nine different sources for user similarity as reflected by activity in social media applications. We suggest a classification of these sources into three categories: people, things, and places. Lists of similar people returned by the nine sources are found to be highly differ ..."
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Cited by 18 (2 self)
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In this work we examine nine different sources for user similarity as reflected by activity in social media applications. We suggest a classification of these sources into three categories: people, things, and places. Lists of similar people returned by the nine sources are found to be highly different from each other as well as from the list of people the user is familiar with, suggesting that aggregation of sources may be valuable. Evaluation of the sources and their aggregates points at their usefulness across different scenarios, such as information discovery and expertise location, and also highlights sources and aggregates that are particularly valuable for inferring user similarity. Author Keywords Social networks, user similarity, social media, social
Enhancing directed content sharing on the web
- CHI
"... To find interesting, personally relevant web content, people rely on friends and colleagues to pass links along as they encounter them. In this paper, we study and augment linksharing via e-mail, the most popular means of sharing web content today. Armed with survey data indicating that active share ..."
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Cited by 17 (5 self)
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To find interesting, personally relevant web content, people rely on friends and colleagues to pass links along as they encounter them. In this paper, we study and augment linksharing via e-mail, the most popular means of sharing web content today. Armed with survey data indicating that active sharers of novel web content are often those that actively seek it out, we developed FeedMe, a plug-in for Google Reader that makes directed sharing of content a more salient part of the user experience. FeedMe recommends friends who may be interested in seeing content that the user is viewing, provides information on what the recipient has seen and how many emails they have received recently, and gives recipients the opportunity to provide lightweight feedback when they appreciate shared content. FeedMe introduces a novel design space within mixed-initiative social recommenders: friends who know the user voluntarily vet the material on the user’s behalf. We performed a two-week field experiment (N=60) and found that FeedMe made it easier and more enjoyable to share content that recipients appreciated and would not have found otherwise.
Blogosphere: Research Issues, Tools, and Applications
"... Weblogs, or Blogs, have facilitated people to express their thoughts, voice their opinions, and share their experiences and ideas. Individuals experience a sense of community, a feeling of belonging, a bonding that members matter to one another and their niche needs will be met through online intera ..."
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Cited by 14 (0 self)
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Weblogs, or Blogs, have facilitated people to express their thoughts, voice their opinions, and share their experiences and ideas. Individuals experience a sense of community, a feeling of belonging, a bonding that members matter to one another and their niche needs will be met through online interactions. Its open standards and low barrier to publication have transformed information consumers to producers. This has created a plethora of open-source intelligence, or “collective wisdom ” that acts as the storehouse of overwhelming amounts of knowledge about the members, their environment and the symbiosis between them. Nonetheless, vast amounts of this knowledge still remain to be discovered and exploited in its suitable way. In this paper, we introduce various state-of-the-art research issues, review some key elements of research such as tools and methodologies in Blogosphere, and present a case study of identifying the influential bloggers in a community to exemplify the integration of some major aspects discussed in this paper. Towards the end, we also compare and contrast the blogosphere and social networks and the research therein. 1. INTRODUCTION TO
