What is Your Organization 'Like'?: A Study of Liking Activity in the
Enterprise
Workplace Social Performance
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Guy, Ido
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Ronen, Inbal
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Zwerdling, Naama
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Zuyev-Grabovitch, Irena
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Jacovi, Michal
Proceedings of the ACM CHI'16 Conference on Human Factors in Computing
Systems
2016-05-07
v.1
p.3025-3037
© Copyright 2016 ACM
Summary: The 'like' button, introduced by Facebook several years ago, has become one
of the most prominent icons of social media. Similarly to other popular social
media features on the web, enterprises have also recently adopted it. In this
paper, we present a first comprehensive study of liking activity in the
enterprise. We studied the logs of an enterprise social media platform within a
large global organization along a period of seven months, in which 393,720
'likes' were performed. In addition, we conducted a survey of 571 users of the
platform's 'like' button. Our evaluation combines quantitative and qualitative
analysis to inspect what employees like, why they use the 'like' button, and to
whom they give their 'likes'.
When the Crowd is Not Enough: Improving User Experience with Social Media
through Automatic Quality Analysis
Social Network Methods
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Pelleg, Dan
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Rokhlenko, Oleg
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Szpektor, Idan
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Agichtein, Eugene
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Guy, Ido
Proceedings of ACM CSCW 2016 Conference on Computer-Supported Cooperative
Work and Social Computing
2016-02-27
v.1
p.1080-1090
© Copyright 2016 ACM
Summary: Social media gives voice to the people, but also opens the door to
low-quality contributions, which degrade the experience for the majority of
users. To address the latter issue, the prevailing solution is to rely on the
"wisdom of the crowds" to promote good content (e.g., via votes or "like"
buttons), or to downgrade bad content. Unfortunately, such crowd feedback may
be sparse, subjective, and slow to accumulate. In this paper, we investigate
the effects, on the users, of automatically filtering question-answering
content, using a combination of syntactic, semantic, and social signals. Using
this filtering, a large-scale experiment with real users was performed to
measure the resulting engagement and satisfaction. To our knowledge, this
experiment represents the first reported large-scale user study of
automatically curating social media content in real time. Our results show that
automated quality filtering indeed improves user engagement, usually aligning
with, and often outperforming, crowd-based quality judgments.
Social Media-Based Expertise Evidence
Papers
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Yogev, Arnon
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Guy, Ido
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Ronen, Inbal
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Zwerdling, Naama
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Barnea, Maya
Proceedings of the 14th European Conference on Computer-Supported
Cooperative Work
2015-09-19
p.63-82
© Copyright 2015 Springer International Publishing Switzerland
Summary: Social media provides a fertile ground for expertise location. The public
nature of the data supports expertise inference with little privacy
infringement and, in addition, presentation of direct and detailed evidence for
an expert's skillfulness in the queried topic. In this work, we study the use
of social media for expertise evidence. We conducted two user surveys of
enterprise social media users within a large global organization, in which
participants were asked to rate anonymous experts based on artificial and real
evidence originating from different types of social media data. Our results
indicate that the social media data types perceived most convincing as evidence
are not necessarily the ones from which expertise can be inferred most
precisely or effectively. We describe these results in detail and discuss
implications for designers and architects of expertise location systems.
The Role of User Location in Personalized Search and Recommendation
Industry Session 2: Generic Platforms and Location-based Application Domains
/
Guy, Ido
Proceedings of the 2015 ACM Conference on Recommender Systems
2015-09-16
p.236
© Copyright 2015 ACM
Summary: With mobile devices, users no longer access the web from specific locations,
but virtually from anywhere. How does this affect our ability to provide
personalized information for users' In this talk, I will discuss the influence
of location activity on users' information needs and how a better understanding
of these needs can help enhance web applications in which personalization plays
a central role.
Islands in the Stream: A Study of Item Recommendation within an Enterprise
Social Stream
Session 9A: Streams
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Guy, Ido
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Levin, Roy
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Daniel, Tal
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Bolshinsky, Ella
Proceedings of the 2015 Annual International ACM SIGIR Conference on
Research and Development in Information Retrieval
2015-08-09
p.665-674
© Copyright 2015 ACM
Summary: Social streams allow users to receive updates from their network by
syndicating social media activity. These streams have become a popular way to
share and consume information both on the web and in the enterprise. With so
much activity going on, filtering and personalizing the stream for individual
users is a key challenge. In this work, we study the recommendation of
enterprise social stream items through a user survey with 510 participants,
conducted within a globally distributed organization. In the survey,
participants rated their level of interest and surprise for different items
from the stream and could also indicate whether they were already familiar with
the item. Thus, our evaluation goes beyond the common accuracy measure and
examines aspects of serendipity and novelty. We also inspect how various
features of the recommended item, its author, and reader, influence its
ratings. Our results shed light on the key factors that make a stream item
valuable to its reader within the enterprise.
Searcher in a Strange Land: Understanding Web Search from Familiar and
Unfamiliar Locations
Short Papers
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Kravi, Elad
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Agichtein, Eugene
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Guy, Ido
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Kanza, Yaron
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Mejer, Avihai
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Pelleg, Dan
Proceedings of the 2015 Annual International ACM SIGIR Conference on
Research and Development in Information Retrieval
2015-08-09
p.855-858
© Copyright 2015 ACM
Summary: With mobile devices, web search is no longer limited to specific locations.
People conduct search from practically anywhere, including at home, at work,
when traveling and when on vacation. How should this influence search tools and
web services? In this paper, we argue that information needs are affected by
the familiarity of the environment. To formalize this idea, we propose a new
contextualization model for activities on the web. The model distinguishes
between a search from a familiar place (F-search) and a search from an
unfamiliar place (U-search). We formalize the notion of familiarity, and
propose a method to identify familiar places. An analysis of a query log of
millions of users, demonstrates the differences between search activities in
familiar and in unfamiliar locations. Our novel take on search
contextualization has the potential to improve web applications, such as query
autocompletion and search personalization.
Games for Crowds: A Crowdsourcing Game Platform for the Enterprise
Games and Virtual Worlds
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Guy, Ido
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Hashavit, Anat
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Corem, Yaniv
Proceedings of ACM CSCW 2015 Conference on Computer-Supported Cooperative
Work and Social Computing
2015-02-28
v.1
p.1860-1871
© Copyright 2015 ACM
Summary: In this paper, we present a crowdsourcing game platform that allows users to
play, create, and share simple games that harness the collective intelligence
of employees within the enterprise. The platform uses the wizard design pattern
to guide users through the process of creating a game. We describe the platform
in detail and report our findings from deploying it within a large global
organization for a period of three months, in which 34 games were created by 25
employees and played by 339. We combine qualitative and quantitative analysis
to understand the characteristics of the different games and their impact on
popularity and engagement, to validate our design goals, and to suggest
potential enhancements.
The sixth ACM RecSys workshop on recommender systems and the social web
Workshops
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Jannach, Dietmar
/
Freyne, Jill
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Geyer, Werner
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Guy, Ido
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Hotho, Andreas
/
Mobasher, Bamshad
Proceedings of the 2014 ACM Conference on Recommender Systems
2014-10-06
p.395
© Copyright 2014 ACM
Summary: The emergence of what is called the social web and the continuing stream of
new applications and community-based platforms including Facebook, Twitter,
LinkedIn and others had a substantial impact on recommender systems research
and practice over the last years in different ways.
First, today's web users are more willing to share more about themselves
than before the Web 2.0, thus providing more information sources that can be
leveraged in the user modeling and recommendation process. Furthermore, the
newly available information sources can not only be used to optimize the
recommendations for an individual user, but can also help to identify more
general patterns and trends in the behavior of the community that can be
exploited by other applications.
Second, personalization, information filtering and recommendation are often
the central functionality of many of these social web based applications. On
typical social networks, users for example get recommendations for news to
read, songs to listen to, groups to join, friends to follow, people to connect
or jobs that might be interesting.
These developments lead to different challenges to be addressed in
recommender systems research. On the one hand, for example, the question arises
of how to effectively combine the huge variety of information sources for
improved recommendations. On the other hand, regarding the new opportunities
for applying recommender systems in social web environments, in many cases new
techniques are required to address the particularities of the domain or to deal
with scalability issues.
The ACM RecSys 2014 Workshop on Recommender Systems and the Social Web aims
to be a platform for researchers from academia and industry as well as for
practitioners to present and discuss the various challenges and possible
solutions related to all aspects of social web recommendations. The call for
papers correspondingly covered a variety of topics in this area including all
sorts of applications of recommender systems technology and their interfaces;
collective knowledge creation and topic emergence; context-aware and group
recommendation approaches; and case studies and empirical evaluations.
This year's workshop was already the sixth in a series of successful
workshops co-located with the ACM Conference on Recommender Systems since 2009.
Again, we received several submissions from researchers from academia and
industry which were thoroughly reviewed and selected for presentation at the
workshop by a program committee of international experts in the field.
The papers submitted to the workshop addressed a number of different topics
and put forward novel proposals to build social web recommender system. In the
context of applying recommendation technology to information personalization
and resource ranking problems in Social Web environments, the submitted papers
for example dealt with the problem of ranking community-provided product
reviews based on opinion mining or with the recommendation of friends on social
networks. As an example of how to leverage Social Web information to build
better systems, one of the works proposed to analyze the characteristics of
publicly shared music playlists to better understand how future music
recommendation systems should be designed. Finally, another contribution from
industry addressed challenges and lessons learned when building large-scale
collaborative filtering solutions on Social Web platforms in a real-world
environment.
Social recommender system tutorial
Tutorials
/
Guy, Ido
/
Geyer, Werner
Proceedings of the 2014 ACM Conference on Recommender Systems
2014-10-06
p.403-404
© Copyright 2014 ACM
Summary: In recent years, with the proliferation of the social web, users are
increasingly exposed to social overload and the designers of social web sites
are challenged to attract and retain their user basis. Social recommender
systems are becoming an integral part of virtually any leading website, playing
a key factor in its success: First, they aim to address the overload problem by
helping users to find relevant content. Second, they can provide
recommendations for content creation, increasing participation and user
retention. In this tutorial, we will review the broad domain of social
recommender systems, their application for the social web, the underlying
techniques and methodologies; the data in use, recommended entities, and target
population; evaluation techniques; and open issues and challenges.
Recommending social media content to community owners
Session 3a: Social media
/
Ronen, Inbal
/
Guy, Ido
/
Kravi, Elad
/
Barnea, Maya
Proceedings of the 2014 Annual International ACM SIGIR Conference on
Research and Development in Information Retrieval
2014-07-06
p.243-252
© Copyright 2014 ACM
Summary: Online communities within the enterprise offer their leaders an easy and
accessible way to attract, engage, and influence others. Our research studies
the recommendation of social media content to leaders (owners) of online
communities within the enterprise. We developed a system that suggests to
owners new content from outside the community, which might interest the
community members. As online communities are taking a central role in the
pervasion of social media to the enterprise, sharing such recommendations can
help owners create a more lively and engaging community. We compared seven
different methods for generating recommendations, including content-based,
member-based, and hybridization of the two. For member-based recommendations,
we experimented with three groups: owners, active members, and regular members.
Our evaluation is based on a survey in which 851 community owners rated a total
of 8,218 recommended content items. We analyzed the quality of the different
recommendation methods and examined the effect of different community
characteristics, such as type and size.
Tutorial on social recommender systems
WWW 2014 tutorials
/
Guy, Ido
Companion Proceedings of the 2014 International Conference on the World Wide
Web
2014-04-07
v.2
p.195-196
© Copyright 2014 ACM
Summary: In recent years, with the proliferation of the social web, users are exposed
to an intensively growing social overload. Social recommender systems aim to
address this overload and are becoming integral part of virtually any leading
website, playing a key factor in its success. In this tutorial, we will review
the broad domain of social recommender systems, the underlying techniques and
methodologies; the data in use, recommended entities, and target population;
evaluation techniques; applications; and open issues and challenges.
Understanding employee social media chatter with enterprise social pulse
Social media in the enterprise
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Shami, N. Sadat
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Yang, Jiang
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Panc, Laura
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Dugan, Casey
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Ratchford, Tristan
/
Rasmussen, Jamie C.
/
Assogba, Yannick M.
/
Steier, Tal
/
Soule, Todd
/
Lupushor, Stela
/
Geyer, Werner
/
Guy, Ido
/
Ferrar, Jonathan
Proceedings of ACM CSCW 2014 Conference on Computer-Supported Cooperative
Work and Social Computing
2014-02-15
v.1
p.379-392
© Copyright 2014 ACM
Summary: The rise of social media in the enterprise has enabled new ways for
employees to speak up and communicate openly with colleagues. This rich textual
data can potentially be mined to better understand the opinions and sentiment
of employees for the benefit of the organization. In this paper, we introduce
Enterprise Social Pulse (ESP) -- a tool designed to support analysts whose job
involves understanding employee chatter. ESP aggregates and analyzes data from
internal and external social media sources while respecting employee privacy.
It surfaces the data through a user interface that supports organic results and
keyword search, data segmentation and filtering, and several analytics and
visualization features. An evaluation of ESP was conducted with 19 Human
Resources professionals. Results from a survey and interviews with participants
revealed the value and willingness to use ESP, but also surfaced challenges
around deploying an employee social media listening solution in an
organization.
Most liked, fewest friends: patterns of enterprise social media use
Social media in the enterprise
/
Mark, Gloria
/
Guy, Ido
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Kremer-Davidson, Shiri
/
Jacovi, Michal
Proceedings of ACM CSCW 2014 Conference on Computer-Supported Cooperative
Work and Social Computing
2014-02-15
v.1
p.393-404
© Copyright 2014 ACM
Summary: Enterprise social media can provide visibility of users' actions and thus
has the potential to reveal insights about users in the organization. We mined
large-scale social media use in an enterprise to examine: a) user roles with
such broad platforms and b) whether people with large social networks are
highly regarded. First, a factor analysis revealed that most variance of social
media usage is explained by commenting and 'liking' behaviors while other usage
can be characterized as patterns of distinct tool usage. These results informed
the development of a model showing that online network size interacts with
other media usage to predict who is highly assessed in the organization. We
discovered that the smaller one's online social network size in the
organization, the more highly assessed they were by colleagues. We explain this
inverse relationship as due to friending behavior being highly visible but not
yet valued in the organization.
The perception of others: inferring reputation from social media in the
enterprise
Technology and information workers
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Jacovi, Michal
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Guy, Ido
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Kremer-Davidson, Shiri
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Porat, Sara
/
Aizenbud-Reshef, Netta
Proceedings of ACM CSCW 2014 Conference on Computer-Supported Cooperative
Work and Social Computing
2014-02-15
v.1
p.756-766
© Copyright 2014 ACM
Summary: The emergence of social media allows people to interact with others all over
the world. During interaction, people leave many traces behind that can reveal
things about themselves, or about how they perceive others: having many
followers may indicate that one is an influencer; forum answers that gain high
ranking, are likely to testify for expertise; people who gain high ranking in
eCommerce sites are likely to be trustworthy. In this paper, we examine whether
public online traces can be used for inferring the reputation of a person as
perceived by others in relation to trustworthiness, influence, expertise, and
impact. We describe a study performed on indicators of reputation that
employees leave in a rich organizational social media platform. We compare
different indicators, and report the results of an extensive user study with
over 500 participants who provided their perception of thousands of others
through a set of hypothetical scenarios.
What motivates members to contribute to enterprise online communities?
Posters
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Ehrlich, Kate
/
Muller, Michael
/
Matthews, Tara
/
Guy, Ido
/
Ronen, Inbal
Companion Proceedings of ACM CSCW 2014 Conference on Computer-Supported
Cooperative Work and Social Computing
2014-02-15
v.2
p.149-152
© Copyright 2014 ACM
Summary: A major challenge for online communities is encouraging members to
participate and contribute content to the community. While prior work has
identified motivators to contribute for internet community members, it is
unknown if these are the same for employees in enterprise communities. A
qualitative study with a group of very active employee members of enterprise
communities we called "informal leaders", revealed that they were motivated by
wanting to help other members but only for those communities which related to
their job. In contrast to prior findings from internet communities, they did
not appear to be motivated by the need to develop their reputation or to
connect with others. These results provide new insights into participation in
enterprise online communities.
The fifth ACM RecSys workshop on recommender systems and the social web
Workshops
/
Mobasher, Bamshad
/
Jannach, Dietmar
/
Geyer, Werner
/
Freyne, Jill
/
Hotho, Andreas
/
Anand, Sarabjot Singh
/
Guy, Ido
Proceedings of the 2013 ACM Conference on Recommender Systems
2013-10-12
p.477-478
© Copyright 2013 ACM
Mining expertise and interests from social media
Research papers
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Guy, Ido
/
Avraham, Uri
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Carmel, David
/
Ur, Sigalit
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Jacovi, Michal
/
Ronen, Inbal
Proceedings of the 2013 International Conference on the World Wide Web
2013-05-13
v.1
p.515-526
© Copyright 2013 ACM
Summary: The rising popularity of social media in the enterprise presents new
opportunities for one of the organization's most important needs -- expertise
location. Social media data can be very useful for expertise mining due to the
variety of existing applications, the rich metadata, and the diversity of user
associations with content. In this work, we provide an extensive study that
explores the use of social media to infer expertise within a large global
organization. We examine eight different social media applications by
evaluating the data they produce through a large user survey, with 670
enterprise social media users. We distinguish between two semantics that relate
a user to a topic: expertise in the topic and interest in it and compare these
two semantics across the different social media applications.
Mining and analyzing the enterprise knowledge graph
LSNA'13 keynote talks
/
Guy, Ido
Companion Proceedings of the 2013 International Conference on the World Wide
Web
2013-05-13
v.2
p.497-498
© Copyright 2013 ACM
Summary: Today's enterprises hold ever-growing amounts of public data, stemming from
different organizational systems, such as development environments, CRM
systems, business intelligence systems, and enterprise social media. This data
unlocks rich and diverse information about entities, people, terms, and the
relationships among them. A lot of insight can be gained through analyzing this
knowledge graph, both by individual employees and by the organization as a
whole. In this talk, I will review recent work done by the Social Technologies
& Analytics group at IBM Research-Haifa to mine these relationships,
represent them in a generalized model, and use the model for different aims
within the enterprise, including social search [5], expertise location [1],
social recommendation [2, 3], and network analysis [4].
Finger on the Pulse: The Value of the Activity Stream in the Enterprise
UX in Work/Educational Contexts
/
Guy, Ido
/
Steier, Tal
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Barnea, Maya
/
Ronen, Inbal
/
Daniel, Tal
Proceedings of IFIP INTERACT'13: Human-Computer Interaction-4
2013
v.4
p.411-428
Keywords: Activity streams; collaboration; cscw; enterprise; enterprise search;
real-time search; social analytics; social business; social media; social
search; social software; social streams; web 2.0
© Copyright 2013 IFIP
Summary: The activity stream, which syndicates user activities across social media,
has been gaining popularity on the web. With social media infiltrating the
enterprise and higher portions of the workforce becoming accustomed to
consuming information through activity streams, it also has the potential to
play a key role in shaping the workplace. This work provides a first
comprehensive study of an enterprise activity stream. We analyze different
characteristics of the stream, its usage through a faceted search-based
application, and the way users search it compared to traditional enterprise
search. We also discuss various use cases of the stream, both from an
individual employee's perspective and from an organizational perspective,
exposing the potential value and role of the activity stream in the enterprise
of the future.
Crowdsourcing in the enterprise
Keynote address
/
Guy, Ido
Proceedings of the 2012 International Workshop on Multimodal Crowd Sensing
2012-11-02
p.1-2
© Copyright 2012 ACM
Summary: This talk reviews several of the recent studies conducted by the Social
Technologies group at IBM Research-Haifa, which demonstrate the use of social
analytics tools to extract value of enterprise social media. From recommender
systems, through activity stream filtering and analysis, to crowdsourcing games
in the enterprise, the voice of the employees can now be heard and utilized
better than ever within the newly formed social business.
Swimming against the Streamz: search and analytics over the enterprise
activity stream
Knowledge management short paper session
/
Guy, Ido
/
Steier, Tal
/
Barnea, Maya
/
Ronen, Inbal
/
Daniel, Tal
Proceedings of the 2012 ACM Conference on Information and Knowledge
Management
2012-10-29
p.1587-1591
© Copyright 2012 ACM
Summary: Activity streams have become prevalent on the web and are starting to emerge
in enterprises. In this work, we present Streamz, a novel application that uses
a faceted search approach to provide employees with advanced capabilities of
search, navigation, attention management, and other types of analytics on top
of an enterprise activity stream. We provide a detailed description of the
Streamz tool as well as usage analysis based on user interface logs and
interviews of active users.
Impression formation in corporate people tagging
Workplace
/
Raban, Daphne R.
/
Danan, Avinoam
/
Ronen, Inbal
/
Guy, Ido
Proceedings of ACM CHI 2012 Conference on Human Factors in Computing Systems
2012-05-05
v.1
p.569-578
© Copyright 2012 ACM
Summary: This research explores the relationship between self-presentation and
perception by others as manifested explicitly through the use of tags in a
people tagging system. The study provides insights relevant for the
organizational context since it is based on a system implemented within IBM. We
developed a detailed codebook and used it to categorize 9,506 tags assigned to
a sample of taggers. Our analysis examines the use of self tags versus social
tags (assigned by others) across different categories and sub-categories. While
overlap exists, self tags tend to be more factual describing technology
expertise, social tags augment the individual tags by adding a personal
dimension.
Best faces forward: a large-scale study of people search in the enterprise
Search interfaces
/
Guy, Ido
/
Ur, Sigalit
/
Ronen, Inbal
/
Weber, Sara
/
Oral, Tolga
Proceedings of ACM CHI 2012 Conference on Human Factors in Computing Systems
2012-05-05
v.1
p.1775-1784
© Copyright 2012 ACM
Summary: This paper presents Faces, an application built to enable effective people
search in the enterprise. We take advantage of the popularity Faces has gained
within a globally distributed enterprise to provide an extensive analysis of
how and why people search is used within the organization. Our study is
primarily based on an analysis of the Faces query log over a period of more
than four months, with over a million queries and tens of thousands of users.
The analysis results are presented across four dimensions: queries, users,
clicks, and actions, and lay the foundation for further advancement and
research on the topic.
Diversity among enterprise online communities: collaborating, teaming, and
innovating through social media
Better together
/
Muller, Michael
/
Ehrlich, Kate
/
Matthews, Tara
/
Perer, Adam
/
Ronen, Inbal
/
Guy, Ido
Proceedings of ACM CHI 2012 Conference on Human Factors in Computing Systems
2012-05-05
v.1
p.2815-2824
© Copyright 2012 ACM
Summary: There is a growing body of research into the adoption and use of social
software in enterprises. However, less is known about how groups, such as
communities, use and appropriate these technologies, and the implications for
community structures. In a study of 188 very active online enterprise
communities, we found systematic differences in size, demographics and
participation, aligned with differences in community types. Different types of
communities differed in their appropriation of social software tools to create
and use shared resources, and build relationships. We propose implications for
design of community support features, services for potential community members,
and organizations looking to derive value from online groups.
Bon voyage: social travel planning in the enterprise
Four life stages
/
Aizenbud-Reshef, Netta
/
Barger, Artem
/
Guy, Ido
/
Dubinsky, Yael
/
Kremer-Davidson, Shiri
Proceedings of ACM CSCW'12 Conference on Computer-Supported Cooperative Work
2012-02-11
v.1
p.819-828
© Copyright 2012 ACM
Summary: A proliferation of travel-related web sites enable people to share their
travel plans, review hotels, offer advice, and more. In this paper we study
social travel planning in the enterprise. While business travelers and leisure
travelers have different preferences and needs, employees may benefit from
sharing information and travel plans within the enterprise. We present a study
collecting the requirements for social travel from employees, detail the design
principles of a social travel application in the enterprise, and present
Voyage, the outcome. We evaluated Voyage based on qualitative and quantitative
data and discuss the results using four perspectives: collaborative activities,
social information impact, usage patterns, and sharing behavior. Employees
expressed their growing satisfaction from the social information contributed by
fellow employees. Moreover, we observed that Voyage shortens the reservation
time, thus saving costs for the enterprise.
