Agenda
The Sentiment Analysis Symposium program for Tuesday, October 30, 2012 is outlined in the agenda that follows. (Also see the pages for the optional October 29 Practical Sentiment Analysis tutorial and Introduction to Social Media Listening class.)
Monday afternoon, October 29 2:00 pm-5:30 pm |
(optional, separate registration fee)
Diana Maynard, University of Sheffield, UK
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Monday afternoon, October 29 2:00 pm-5:30 pm |
(optional, separate registration fee)
Mike Moran, Converseon
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Monday evening, October 29 5:30 pm-7:00 pm |
Networking reception for symposium attendees & friends, at the Bently Reserve. |
Tuesday morning, October 30 8:00 am-8:30 am |
Registration & Coffee |
Morning Session -- Tuesday, October 30 | |
8:30 am-8:40 am | Chair's Welcome: The Sentiment Spectrum
Seth Grimes, Alta Plana Corporation
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8:40 am-9:20 am |
Keynote: Sentiment Driven Behaviors; Sentiment Driven Decisions
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Executives are eager to use sentiment as a deciding factor in a wide spectrum of business decisions-- from investing further marketing dollars to developing new products to enhancing call center
operations. The origin of this idea is well-founded in the relationship between market sentiment and price development in the world of investing. Sentiment analysis in social media has made
substantial headway in applying a modicum of structure to a massive, unwieldy, unstructured set of blogs, forums, microblogs, and social networks. However, the precise relationship between
sentiment and subsequent (market) behaviors is variable. Structure does not necessarily beget behavior, and thus proves precarious for business decisions. This talk will review the outcomes of
specific business decisions based on sentiment and address three major factors as to why the relationship is as of yet undefined.
Kate Niederhoffer, Knowable Research
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9:20 am-9:45 am |
Up Close and Personal: Social Media Insights and the Mind of the Consumer
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Augmenting a structured quantitative survey with social media data from your respondents can strengthen your typical survey analysis with rich qualitative insight. As part
of your survey data collection effort, you also bring in your respondents' social media data in real-time. Combining your respondents' social media interactions with their structured
This technique will show you how to establish in-depth, sophisticated segmentation based on social media narratives gathered at the same time you do online survey research.
Carol Haney, Toluna
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9:45 am-10:10 am |
Emotions Affect Markets in Predictable Ways
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Where there are markets, there are emotions. Where there are emotions, there are cycles. Where you understand cycles, you profit.With modern economic and financial theory increasingly looking towards behavioural and crowd-based models to explain cyclical booms and busts, the ability to quantitatively assess broad market sentiment can be a valuable indicator to help guide successful trading and investment strategies. The world of big data is a new market data frontier that can provide trading firms with a real edge by helping to model behavioural economics. News and Social Media Sentiment toolsallow financial professionals to analyze news and social media in real-time to convert the volume and variety of professional news and the internet into manageable information flows that drive sharper decisions.
Aleksander Sobczyk, Thomson Reuters
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10:10 am-10:20 am |
Sentiment: Creating the Future
Catherine Van Zuylen, Attensity
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10:20 am-10:40 am | Break |
10:40 am-11:10 am |
Keynote
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11:10 am-11:30 am |
Using Sentiment Analysis to Make Net Promoter More Actionable
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J.D. Power uses sentiment analysis of survey verbatims combined with the Net Promoter Score (NPS) to better understand the customer service experience for a major US bank and
provide actionable recommendations for improvement of the branch experience. In this talk, using this real-world example, we will explore the relationship of sentiment to NPS and
discuss how to use them together to uncover opportunities for improvement that would have otherwise been missed.
Bill Tuohig, J.D. Power and Associates
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11:30 am-11:50 am |
Amplify Sentiment by Measuring Impact
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Dow Jones' Insight Media Index is a methodology for weighting sentiment by message strength, audience, placement, and other criteria chosen by the user. By choosing up to
a dozen weights, a client can analyze large volumes of coverage to distinguish between kerfuffles and perfect storms.
I'll show how the methodology works, discuss its applications and limitations, and present some real-world case studies.
Barry Parr, Dow Jones
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11:50 am-11:57 am |
Using Social Sentiment to Track Real Time Public Opinion
Rob Bailey, CEO, DataSift
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11:57 am-12:25 pm |
Lightning Talks
Analyzing Weibo, the Chinese Twitter
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I will share my experiences in analyzing Weibo posts. First, I will cover the challenges of working with Chinese text. Then, will share some of my personal solutions as
well as available resources. Finally, I will point of some Weibo-specific shortcuts that can be utilized.
Ken Hu, Soshio
Dissipating Ambiguity: Direct Extraction of Sentiment from Social Networks
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Modern systems of social network sentiment extraction lean heavily on
artificial intelligence scraping and inferring sentiment from public feeds
and streams. There is an alternative. Startup Swipp, Inc. has a new
approach to sentiment collection and analysis that eliminates ambiguity,
adds additional layers of value, and actually spurs the community to
disclose more of what they think and feel -- all while making the broader
user and commercial networks smarter. This new angle will not only allow
sentiment to surface for more direct analysis, but will actually motivate
and inspire new behavior, shaping it along the way.
Dr. Erin Olivo, SmogFarm
Analysis and Visualization of Social Media Content
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This presentation briefly summarizes value of social media content analysis and importance of data visualization. Then, it describes individual entities used
for specific analysis and states some of tools that are being used. The main centre of the presentation is dedicated to different possible ways of visualisation of web content
discussions (with focus on social media discussion); it focuses in particular on ways to show through visualisation relationships between behavior and number of users, topic discussion
and sentiment over time. New ways of graphical illustrations, e. g. time axis in circles or different types of polygons, will be presented. The development of analytical and
visualization portlets will be also mentioned. Outputs from existing content will be presented as well.
Tereza Pařilová, Masaryk University
Beyond Sentiment: The Next Generation of Social Intelligence
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As brands continue strive to understand their sentiment in social media, a new generation of social intelligence is rapidly emerging. Emotions, intention, message types and other new classifiers are providing a fuller spectrum of insights and meaning that can be game-changing. This session will discuss, briefly, some of the new classifiers that are bringing new dimensions to social intelligence.
Mike Moran, Converseon
Mining Big Voice of the Customer Data
Daniel Ziv, Verint
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12:25 pm-12:35 pm |
Building Sentiment Analysis on the Right Social Data
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Do you analyze sentiment on social data? What datasources do you use? Where do you get them? The answers to these questionsare just as important as the analysis you run. In this session we will explore the different types of social data available and best practices for consuming such data. After attending this session, you will have an in-depth understanding of the different types of conversations available in different social data sources. We?ll also cover the role that reliability, sustainability and completeness play in yourunderlying data so you can be sure you?re building your analysis on a solidfoundation.
Chris Moody, President & COO, Gnip
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Lunch & Networking | |
12:35 pm-1:30 pm | Lunch & Networking |
12:35 pm-5:30 pm | Exhibit Open |
Afternoon Session | |
1:30 pm-1:50 pm |
Harvesting Mobile Micro-Slang
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Marketers are tasked with understanding sentiment need to understand terminology and language used to describe their product. Approaches in text mining and term analysis
that are used in taxonomy and vocabulary development can be used to solve language problems in sentiment analysis. In this session, Jeannine Bartlett provides an example of how to use
a text mining tool to beef up a sentiment analysis taxonomy, thesaurus and signal detection strength for mobile micro-slang target audiences.
Jeannine Bartlett, Earley & Associates
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1:50 pm-2:10 pm |
Sentiment Analysis and the Consumer Genome
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At Infosys, we've created what we call the Consumer Genome and it could well be the next leap in thinking. Just like its human counterpart, the basic premise of a consumer
genome is that certain intrinsic attributes strongly determine consumer behavior. The list includes demographics, connections, influences, interests, needs and buying behavior. That's
a marked departure from current consumer understanding practices, with an over reliance on demographic metrics as predictors of behavior.
The consumer genome has its own complex DNA, made up of rich information about an individual that can provide unique and compelling insights into that person's consumption behavior. By
decoding it, consumer product companies, retailers, indeed all types of marketers can personalize their offerings, channels and campaigns to each and every individual. Call it 'extreme
relevance.'
The presentation will describe the concept of the consumer genome and will explain how semantic analysis and artificial intelligence on a big data platform are leveraged to realize its
promise.
Vaidyanatha Siva, Infosys Ltd.
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2:10 pm-2:30 pm |
A Tailor-Made One-Size-Fits-All Approach to Sentiment Analysis
Diana Maynard, University of Sheffield
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2:30 pm-2:50 pm |
Assess and React to Market Situations Using Social Data
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This session will show how a variety of data sources, including revenue, brand tracker, and social media work together to evaluate brand reputation and support recommendations for organizational reactions. Specifically, examples of sentiment analysis and buzz volume are used to show the impact and context that social data provides.
Liz Keck, American Cancer Society
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2:50 pm-3:10 pm |
Cisco's Integrated Sentiment Analysis
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Cisco has evolved from analyzing purely traditional media, to developing a truly integrated global approach that now also incorporates social media, industry and financial analyst data, employee conversation and customer verbatims. By minimizing siloed analysis, we are able to understand patterns and drive a cohesive strategy that is relevant to all audiences. In this presentation I will share examples of this integrated analysis as well as discuss some of the challenges we face working with diverse data sets in multiple languages.
Elizabeth Rector, Cisco
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3:10 pm-3:40 pm | Break |
3:40 pm-4:00 pm |
Google's Text Analytics War on Spam
Mike Moran, Converseon
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4:00 pm-4:40 pm |
Campaign 2012: The Voice of the Voter
Participants present their analyses of candidates and issues, one week before the November 6, 2012
presidential election. Who's winning the online/social sentiment race and Why? What tools and methods can help us hear the voice of the voter? Our speakers give us their takes.
Twitter, Politicians, and the Voice of the Voter
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Political discourse is challenging from a sentiment analysis point of view
because political issues are highly dynamic and political language may
contain neologisms that do not occur frequently in general purpose lexical
sentiment models. Also, the presence of humor, sarcasm, and comparatives
may introduce errors in sentiment analysis. In Twitter, these issues are
amplified by the use of Twitter-specific features and constrained message
lengths. In this session, we will present a collaborative project between
the University of Southern California (USC) Signal Analysis and
Interpretation Laboratory, USC Annenberg Innovation Laboratory, and IBM
Corporation. Our system is relies on manual curation of keywords and
hashtags, crowd-sourced annotation, statistical machine learned sentiment
models, and a real-time visualization that is ideal for display during
live events. We describe our corpus and several experiments using
different settings of our sentiment models.
Abe Kazemzadeh, University of Southern California and Graham Mackintosh, IBM
Getting Real(-time) with Live Polling
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Which candidate responses in a presidential debate did the audience perceive as dodging the question? What specific moments in a new comedy did TV viewers find hilarious,
moving, boring, or painful? Questions like these are hard to answer. Traditional polling provides interpretable data, but it can't give you second-by-second information about
people's reactions, and it doesn't scale. Response dials allow fine-grained temporal feedback, but on just one dimension. Social media analysis gets nearer to real time, and on a
massive scale, but it doesn't allow researchers to pose specific questions to the audience.
Rishab Ghosh, Topsy Labs
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4:40 pm-5:30 pm |
Presentations and Panel --
Social Intelligence at the Social Centers: eBay, Twitter & Zynga
Twitter, eBay, and Zynga represent three social centers. Twitter invented and epitomizes high-velocity, high-volume, high-value social communications. eBay defined and defines social commerce. Zynga is the social gaming company. Representatives of the three companies will present and then participate in joint Q&A, moderated by social-media strategist and consultant Dr. Natalie Petouhoff.
Competitive Advantage
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Your customers are on social media. As you plan sentiment analysis and text mining, remember, so are your competition's customers or your prospects. This talk will cover how you can understand the overall market landscape by social data mining for yours and competition conversations. You can go beyond general competition data to understand difference in customer preference, perceptions among different market players. Social Data for Competitive Analysis can help you setup realistic benchmark numbers to make sense of your internal customer data.
Sudha Jamthe, eBay
Sentiment Analysis for Brands on Twitter
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Brands use sentiment analysis on Twitter to listen to and engage with their customers and prospects every day. This talk will share case studies of how some of the more
successful brands use sentiment analysis to measure their performance on Twitter; make decisions about media outside of Twitter; and get critical market input for product decisions. In
the talk and Q&A afterward, I will also share some of the challenges that need to be addressed in order for sentiment analysis to get to the next level.
Ameet Ranadive, Twitter
Using Player Sentiment to Build Great Games
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Zynga games are being played by over 300M people every month across multiple platforms/devices. See how Zynga is using player sentiment as a constant feedback stream into making games players love.
Chris Jones, Zynga
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Reception | |
5:30 pm-7:00 pm | Networking Reception |