Data Mining Online Audiences with D8A Group
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Data Mining Online Audiences with D8A Group

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Using a combination of the data-analysis products available from D8A Group, we’ve been monitoring the unfolding events in real-time to illustrate the ways our technology platforms can be used by ...

Using a combination of the data-analysis products available from D8A Group, we’ve been monitoring the unfolding events in real-time to illustrate the ways our technology platforms can be used by companies, PR firms, marketing agencies, political groups, celebrities, and NGOs to make data informed decisions in real-time crisis scenarios.

In this case study document, we analyze breaking news scenarios involving Chris Christie's Brigegate scandal, Kerry Washington's appearance at the Golden Globes, and the Knight Foundation who we weren't aware had any news events at the time, but we quickly became aware of two through the use of our software.

The primary purpose of using technologies like the D8A suite of analytic products is to monitor and capture real-time data for analysis and research. They are also predictive, helping to surface trends, patterns, and happenings before one might find out about them otherwise. D8A’s products work across multiple communication channels.

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  • 1. BRANDS 2014 CASE STUDY HOW TO MINE ONLINE AUDIENCES TO IMPROVE PUBLIC RELATION STRATEGIES 
 Version 1
  • 2. 2   Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   !   Social Data Monitoring with D8A ! Real-Time Analysis and Data Mining Online Audiences ! ! ! ! ! ! ! ! ! ! ! ! !
  • 3. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   ! ! TABLE OF CONTENTS ! Data-Driven Audience Monitoring Real-Time Media Monitoring Case Studies 1- Public Figures & Reputation Monitoring 2- Real-Time Opinion Polling for Political Groups 3- Corporate Awareness Contextual News Discovery Momentum Real-Time Zeitgeist Filtering by Keyword Exclusion Keyword and Phrase Networks Identifying Influencers Sentiment Analysis Geography Trends and Locations of Interest Predictive Analytics Risk Mitigation and the Timing Of Information ! ! CONTACT ! D8A Group http://d8a.com ! Phone: (520) 301-7906 Email: jon@d8a.com 
 3 4 5 7 12 15 16 18 19 20 21 23 25 27 29 3  
  • 4. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   4   Data-Driven Audience Monitoring ! The proliferation and adoption of mobile phones and social media technologies presents new ways of capturing conversations surrounding events in real-time. There is high demand for products that allow companies, celebrities, public figures and others to explore events by monitoring many media sources (blogs, photos, web feeds, news sources, and tweets) from one environment. ! Using a combination of the data-analysis products available from D8A Group, we’ve been monitoring the unfolding events in real-time to illustrate the ways our technology platforms can be used by companies, PR firms, marketing agencies, political groups, celebrities, and NGOs to make data informed decisions in realtime crisis scenarios. ! The solutions used for this analysis include: • SiftDeck: a product that connects online conversations to the people, places, and things being referenced offline. This helps organizations manage real-world risk to predict and avoid their offline assets from being threatened (think staff, office locations, or property). • Themes: a product that allows users to visually sort through large amounts of text data or streaming data to surface patterns and trends in the content. It allows for the visual navigation of real-time data using search, word trees, keyword & phrase network analysis, and various filters. • Muxboard: a remixable analytic dashboard that allows researchers to apply various algorithms and third-party APIs to real-time, ever-evolving data sets using drag and drop ease. Muxboaard makes it easy to quickly create dashboards tracking different people or brands, each with intricate customizable analytics.
  • 5. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   5   ! Real-Time Media Monitoring The primary purpose of using technologies like the D8A suite of analytic products is to monitor and capture real-time data for analysis and research. They are also predictive, helping to surface trends, patterns, and happenings before one might find out about them otherwise. D8A’s products work across multiple communication channels. ! Though most users are primarily interested in analyzing Twitter’s real-time global data stream, our products also work with mobile data streams (text messages), news articles and headlines, blogs, RSS feeds, JSON feeds, email, and can hook virtually any API made available. This makes our products flexible for any type of online activity monitoring. ! The added advantage of D8A’s particular set of products is the ability to research, sift through, and sort data streams in real time, allowing companies to make data-driven decisions while events are still unfolding. !
  • 6. 6   Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   ! ! Case Study 1: Reputation Monitoring for Public Figures Using our products is like having a ‘crisis management’ consultant on staff at all times - much like the one Kerry Washington plays on the hit TV show Scandal. Using Kerry Washington herself, we did some real-time research on her following the Golden Globe Awards in January of 2014. ! ! ! We began tracking Kerry Washington shortly after the 2014 Golden Globes where she was nominated for Best Performance by an Actress for her work on Scandal. So it’s no wonder that her name increasingly appeared alongside other 
 celebs like Cate Blanchet, Amy Adams, and Idiris Elba.
  • 7. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   7   Hrmm, what’s up with that Idiris Elba connection….could it be a SCANDAL!?! No, actually it turns out both Idiris and Kerry revealed the fact that they were preggers on the Globe’s red carpet. Idiris, debuting his pregnant girlfriend, Kerry revealing her own ‘baby bump’ with her husband.
  • 8. 8   Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   This shows up in the data, the keyword maps allude to “Elba” and “Washington” 
 and couples making appearances at the “Golden Globes”.
  • 9. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   9   ! Case Study 2: Real-Time Opinion Polling for Political Groups In early January 2014, Chris Christie became linked to a scandal that became known as ‘Bridgegate’. Many organizations concerned with politics have faced similar scenarios where the integrity of their candidate, party, or staff is called into question. For organizations working in the political sphere, our products help them monitor in real-time exactly what is going on, how the public is responding, and suggest ways that they might intervene to change the story. !
  • 10. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   10   Our case study monitoring Chris Christie during this timeframe was in many ways fascinating. The real-time feed of contextual news offered insight into what the press was saying. This is a panel that can appear next to any streaming data feed, so that analysts can compare trends in social media activity to trends in news media coverage. !
  • 11. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   11   ! Unsurprisingly, as the news leaked of the story, the partisanship of online audiences increased. See the above image where ‘liberals’ is one of the strongest signals. ! Perhaps more interesting is some of the finding about Rachel Maddow’s ratings boost from the scandal or the Tea Party turning on Christie.
  • 12. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   12   But the information a candidate like Christie wants to know in an unfolding crisis is whether or not the scandal seems to be picking up steam or slowing down, and how public opinion is changing in the political scandal’s wake. !
  • 13. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   13   Our products can account for this, too. On the evening of January 14th 2014, the scandal was still up and down (hour on hour), but the over-arching trend was flat. In the chart below, you can also see that the tide of public opinion about the entire debacle is 34% majority negative versus 5% positive ! 

  • 14. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   14   ! Case Study 3: Corporate Awareness Companies large and small have a lot to protect when it comes to how they are represented online. D8A’s products allow them to monitor their various brands, products, customers, partners, and competitors to ensure that their reputations aren’t affected by any unfortunate occurrences. ! Companies with operations in multiple states and countries also may want to stay up to date on what is happening in multiple locations. ! !
  • 15. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   15   The Knight Foundation is a philanthropic organization that funds technology innovations for news and civic engagement communities around the globe. Apparently, the data set illustrates that “Detroit” seems to be high on their list of priorities. ! Indeed, a quick look at recent headlines of theirs confirm that the Knight Foundation and other philanthropic partners have pledge more than $330 million to save the Detroit Institute of Art from shutting down, or selling off its assets. ! I didn’t know anything about this, and heard about it through my social networks. It was only through the use of our own products that even knew to investigate Knight’s links to Detroit. ! !
  • 16. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   16   ! I also inadvertently discovered that their 2014 class of News Challenge winners was about to be announced either today or tomorrow. It turns out that it was “today”, this image is a graphic of our systems on the morning of January 14th, the same day the Knight Foundation announced the recipients of $2.3 million dollars in funding through it’s News challenge. ! Why does “tomorrow” appear bigger than “today” you might ask? Because our systems deal with real-time data, there was a fair amount of information in the archive from the day before. Because I was looking at the data in the morning, the old data outweighed the new as a signal, something an analyst would know to correct for. By the end of the day the older data would diminish. ! !
  • 17. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   17   ! Contextual News Discovery SiftDeck learns to aggregate news headlines based on keywords parsed from aggregated content. This is different from only aggregating content based on the keywords users enter because it provides a contextual stream of headlines based on the real-time conversation. In other words, SiftDeck recommends potentially related news headlines that a user may not even be aware of. So it serves as a real-time discovery and recommendation engine. ! This feature tries to answer the question: “what if I don’t know what I’m looking for?” Rather than the user programming every single detail into our products, they learn from both the user and the content creators to make new suggestions of which news items might be relevant to the research underway. !
  • 18. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   18   ! ! Momentum Momentum is the term we use to refer to the qualities of a conversation. Does the conversation activity seem to be building or slowing? Are new people joining or are they leaving? Are the people involved from the beginning conversing more or less than they were from the start? Which keywords, influencers, and communication channels are leading the conversation? !
  • 19. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   19   ! ! The image above chronicles the drop and eventual rebound of momentum surrounding the various keywords being tracked. ! ! !
  • 20. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   20   Likewise, looking back over the previous days or weeks shows that there are lulls and bumps in the flow of the conversation over time. This directly correlates to events occurring in the real-world and the virality of news spreading online. ! !
  • 21. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   21   ! Real-Time Zeitgeist What are the recurring themes and phrases in a real-time conversation? The words, phrases, names, and locations that repeat may allow analysts to draw correlations between seemingly unrelated conversations. ! ! ! Were one not even looking for a scandal involving Chris Christie, if a word cloud all of a sudden started surfacing words like ‘scandal’, ‘bridge’, ‘taxes’ and ‘campaign’ (like in the above image) they could easily determine a big story might be breaking and take action. ! This ability to actively monitor the ‘zeitgeist’ or thematic relationships between conversations happening across disparate communication channels often proves
  • 22. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   22   powerful for organizations who have to plan suggested interventions or activities in real-time. ! Filtering By Keyword Exclusion More importantly, these word clouds make it possible to conditionally filter out conversations that actually are unrelated. ! ! ! In this case, the recurrence of the word ‘Munich’ in data streams monitoring conversations about Sudan was because of a football match between Sudanese and German teams1. After identifying messages that are skewing the research,   with our product,Themes, the user can simply click on the word (in this case ‘Munich’) and opt to exclude all data where non-relevant words appear in the same sentences together, while keeping all other data intact. ! !1  Bayern  Start  2014  on  Winning  Note        http://news.sudanvisiondaily.com/details.html?rsnpid=230943  
  • 23. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   23   Organizations using other products for social media analytics often forget that many such tools don’t allow for the selective ‘cleansing’ of datasets to remove misleading or non-relevant content. ! Keyword and Phrase Networks ! ! Themes’ network graphs of words and phrases can provide a powerful means for visually controlling the underlying dataset. In this case, clicking on any word in the above graph, gives you the option to focus only on content that contains that word, or only on the content that doesn’t contain a particular word. ! In the above example, a very large dataset was used to show how select key words appear in high frequency in the same datasets. But by clicking on each word, and choosing to focus or exclude certain ones, the dataset is refined as needed. !
  • 24. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   24   ! ! A researcher might want to only view content where the phrases ‘taxes’, ‘liberals’, ‘scandal’ and ‘work’ appear together as it relates to Chris Christie. If so, it’s simply a matter of point and click (the collection of keywords in the bottom right), and the data is re-organized to fit that criteria. Terms can just as easily be excluded from the dataset. ! Identifying Influencers Monitoring digital conversations allows organizations to identify potential ‘thought leaders’, activists, actors or other people who may be influential in a given scenario. While it’s usually impossible to verify exactly who these actors are, and what their motives are, it’s useful to identify them, to conduct strategies for engagement and outreach.
  • 25. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   ! 25   ! Having this information allows analysts to follow the public conversations of specific individuals. For instance, if any of these (or other) individuals are influential bloggers, employees of other companies, investors, journalists etc. ! !
  • 26. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   26   ! Sentiment Analysis Sentiment analysis is a method of measuring the emotional tone of written text using computer programs. It attempts to weight different words in a body of text against one another, to ultimately provide a ‘score’ to the whole body of text that is either positive, negative, or neutral. ! Why is this useful? Because it allows users to algorithmically determine whether an online conversation is skewing positive or negative in tone. ! ! ! In the image above, it’s easy to quickly see that of the more than 6,972 messages analyzed in the first column, 1679 (25%) have been marked as being negative in tone, while 700 (10%) are positive. If the analyst wants to focus on
  • 27. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   27   the dataset that’s been marked negative, they simply click on that area of the graph. ! The content and related analysis is then sorted to focus on the ‘negative’ content. To give a usecase scenario, this would allow a researcher to view a list of influencers leading the negative tone of a conversation. In the past, this has allowed our users to identify individuals whom they would qualify as the ‘antagonists’ or ‘instigators’ who might be inciting violence or other unwanted activities. Being able to sort data in this way provides a powerful lens of context and discovery. More importantly, it allows analysts to constantly ask questions of the data itself through our simple drag and drop interface. ! ! ! The above screenshot looks at only the analysis of content negative in tone from a different data set than the previous image. You can see that 379 messages represent the negative content, of which 376 comes from Twitter, 3 items come from Google News, and we have a list of potential conversation influencers, as
  • 28. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   28   well as how much content they’ve contributed to the overall conversation. Analysts can now reach out to them directly, or begin monitoring these new sources of interest. Again, all of this is being done in real-time. ! Geography Trends and Locations of Interest Connecting this type of online research to offline activities and actions is a big portion of why people use data products like the ones provided by D8A. We use the social graph and natural language processing to algorithmically map various locations of interest to researchers. ! ! ! !
  • 29. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   29   ! ! This might serve as a point for additional research. For example, how does a spike in activity in Texas relate to Chris Christie? Turns out that’s where the outspoken branch of a major division of the Tea Party is based. ! The power of this information is that even with the most minimal knowledge of a situation, the maps and graphs generated tell a story. While knowing the broader context and having professional expertise in the given subject matter is absolutely necessary, when such knowledge is coupled with these kinds of visual data exploration tools, it’s possible to make the job of experts faster, more nuanced and efficient. ! D8A’s products (SiftDeck, Muxboard/MetaLayer, and Themes) are not meant to replace professional analysts and researchers, but to save them incredible amounts of time. ! !
  • 30. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   30   ! Predictive Analytics When all of our products are combined, it’s possible to anticipate events, demands, or activities that have not happened yet. This is type of anticipatory response to data is based on an area of research called predictive analytics. ! By combining all of our insights into an informed narrative, researchers might be able to determine the correct actions to take well before it’s obvious. As with all systems, it’s possible these predictions can be wrong so rather than give researchers objectives, our products serve to provide the appropriate information for informed conversation and action. ! ! !
  • 31. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   ! ! 31   ! In a scenario where an analyst is viewing multiple dashboards in an unfolding scenario, it’s possible to piece each of these different insights together to suggest action and give reasons for that action. ! In one use of our products in South Sudan, well before stories played out in the media, our team identified several influencers in-country and around the world. ! We knew that the situation was no longer contained to just South Sudan, but was now affecting the whole of the East Africa region; we knew that there appeared to be a rapid build of momentum in the conversations on the evening of January 9th leading into the 10th, and we know that the thematic tone of conversation was trending towards some sort of conflict. We also had the related breaking news stories confirming as much. ! !
  • 32. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   32   ! Risk Mitigation and the Timing of Information While it’s possible to come to the same conclusions in a number of other ways, the timing of information often dictates its value, as well as the time it takes to aggregate all data sources to predict future conclusions. ! For a Wallstreet broker, receiving information that the CEO of a major company is about to be fired might indicate he needs to sell his position in that companies stock. However, receiving the information after the fact (ex. “the CEO was fired yesterday”) is an entirely different scenario. The first scenario allows him to mitigate risk in anticipation of a potential disaster. The other scenario allows him to make the same decisions, but the information is less valuable because he has less control over how the news affects things. A portion of the risk is already realized, thereby making the information less valuable. For the Wallstreet broker, the value of information could be valued in the millions or billions of dollars. For humanitarian organizations and journalists, the type of risk we try to help them mitigate might be measured in loss of life & property, or at the very least, quality of life for the people affected by these events. For brands or public figures, their reputation is directly correlated with their value and ability to derive revenue from customers. ! D8A’s products are designed to shift critical analysis of any situation, event, or phenomena from a retroactive exploration, to a real-time one. In the above scenario, the case was made that value of information is very much related to its timing. !
  • 33. Real-­‐Time  Analysis  and  Data  Mining  Online  Audiences   33   Thus, even if our products only slightly move the needle in regards to the time of information, there is a direct correlation to the amount of value that analysis provides. Knowing how to potentially affect a situation in real-time can be exponentially more valuable than waiting for everything to play out, only to deal with the aftermath. ! While such actions need to be tempered with consideration for culture, context, privacy and law, there is great value in time-shifting the analytics so that companies can react to events more readily because they were able to anticipate potential risk scenarios.