2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
110
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210-MCC
Social Media Analytics for Competitive Advantage
Invited: Social Media Analytics
Invited Session
Chair: Vilma Todri, New York University, New York, NY, 11111,
United States,
1 - Social Influence And Changing Circumstances In The Creation,
Maintenance, And Disruption Of Habits In Global Health Behavior
Christos Nicolaides, Massachusetts Institute of Technology,
In this research I analyze a unique, granular dataset of individual-level exercise
data from more than 10 million users worldwide for about seven years to (a)
measure the regularity of exercise behavior, (b) identify factors that predict a
behavior continuing, (c) compare social influence in running for individuals with
and without running habits, and (d) estimate the consequences of common
disruptions to circumstances cues for habitual behaviors. I use modern causal
inference techniques to address central questions in the psychology of habits with
applications to interventions — especially social interventions — to influence
exercise behavior and adoption of consumer exercise products.
2 - Location-based Advertising And Contextual Mobile Targeting
Dominik Molitor, New York University,
Understanding how location-based advertising (LBA) can be utilized to increase
sales in stores is important for offline retailers. LBA is a means to target users by
making use of their location via GPS-enabled smartphones. Further, the
ubiquitous nature of smartphones increases the importance of additional
contextual factors such as time and weather. In particular, we analyze how
contextual factors can be used to improve the prediction of responses to mobile
promotions by applying unique GPS data. In particular, we examine the interplay
between location, time, weather as well as co-location and users’ responses to
mobile promotions.
3 - The Effect Of Referral Source On News Article Readership And
Sharing Patterns
Sagit Bar-Gill, Massachusetts Institute of Technology, Cambridge,
MA, United States, , Shachar Reichman, Xitong Li
The ongoing transition to online and mobile news consumption is both a
challenge and an opportunity to news providers. Readers are consuming more
content online, and are increasingly relying on third-party aggregators and social
media to find what content to read. We employ analytic tools and fine grained
news consumption data to study the effect of online referral sources on
readership and sharing patterns on the Christian Science Monitor website. We
explore differences in traffic patterns coming from social media and news
aggregators, and examine whether the effects of referral source differ for
mainstream compared to niche content.
4 - Trade-offs In Digital Advertising: Modeling And Measuring
Advertising Effectiveness And Annoyance Dynamics
Vilma Todri, New York University,
Anindya Ghose, Param Vir Singh
This study captures the trade-offs between effective and annoying digital
advertising exposures. A hidden Markov model (HMM) is proposed that allows us
to investigate the extent to which display advertising has an enduring impact on
consumers’ purchase decision and whether display advertising can stimulate
annoyance to consumers; we provide a conceptual framework for understanding
whether persistent digital display advertising exposures constitute a mechanism of
annoyance. We also study the structural dynamics of the effective and annoying
display advertising effects by allowing the corresponding effects to be contingent
on the latent state of the funnel path consumers reside.
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211-MCC
Text Analysis within Social Media
Invited: Social Media Analytics
Invited Session
Chair: Fay Cobb Payton, North Carolina State University, Campus Box
7229, Raleigh, NC, 27695, United States,
1 - Text Analytics - The Power Of Storytelling
FayCobb Payton, Professor, Information Systems, NCSU,
Numbers do not lie. This is a typical framework for positivists (often quantitative)
researchable questions. This session will provide the introduction and a case study
of why text analytics can be a powerful tool for complex, often unstructured data
sources. A following session will provide insights into incorporating text analytics
into organizational and research objectives.
2 - Unlocking Your 80%: Unearthing New Insights With Text Analytics
Christina Engelhardt, SAS Institute,
How can your organization harness the staggering volumes of textual data
coming from social & online media and your own proprietary systems? Join us as
we explore some of the challenges and exciting opportunities these rich, yet
complex, data sources provide us. Session topics include: • Why you should
consider incorporating text analytics into your data science, research, and
operational work streams• How to align technology, data sources, and the various
text methods with your use case and objectives• Examples of how leading
organizations are leveraging Text Analytics
3 - Hierarchical Machine Learning Approach To Detecting Anomalous
Behavior In Online Social Media Forums
Naveen Kumar, University of Memphis, Memphis, TN, 38152,
United States, Deepak Venugopal,
Robin Poston
The detection of anomalous behavior in online social media is a challenging
problem due to complex interactions between several user characteristics such as
review veracity, velocity, volume, and variety. We propose a novel two stage
hierarchical machine learning approach that increases the likelihood of detecting
anomalies by analyzing different actions of individual users and then
characterizing their collective behavior. Specifically, we model user characteristics
as univariate/multivariate distributions and then combine these distributions
using mixture models to obtain a unified view of a user’s behavior. We apply our
approach to real-world reviews and obtain promising results.
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212-MCC
Dr. William Massey: A Dynamic Legacy
Sponsored: Minority Issues
Sponsored Session
Chair: Jamol Pender, Cornell University, 206 Rhodes Hall, Ithaca, NY,
14853-3801, United States,
1 - Dynamic Rate Queues
Jamol Pender, Cornell University,
Inspired by healthcare and transportation systems, this talk will summarize the
past, present, and future of dynamic rate queues and their impact on our society.
2 - Dr. William Massey: A Dynamic Legacy
Robert Hampshire, University of Michigan,
In this talk we will explore the applications of time varying queues to problems in
urban transportation. We show how Bill Massey’s fundamental contributions to
queueing theory and applied probability can be applied to smart parking systems,
bike sharing and car sharing services
3 - The Dynamics 0f Queueing Transience With Dynamic Rates
William A Massey, Professor, Princeton University, ORFE
Department, Sherrerd Hall, Princeton University, Princeton, NJ,
08544, United States,
Inspired by communication and healthcare services, this talk summarizes the
methods developed with many collaborators over the decades to understand the
transient behavior of dynamic rate queues. This analysis is needed when
confronted with the dynamic parameters found in time-inhomogeneous
Markovian queueing models. The static equilibrium analysis for the steady state
of constant rate queues no longer applies.
Constants summarizing the transient behavior for these steady state systems yield
to the natural substitute of deterministic dynamical systems. We can then
approximate the optimal behavior of these queues by controlling this related
family of ordinary differential equations.
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