Gathering Data On Web Jerks. An Interview with SUNY Binghamton’s Jeremy Blackburn

How often do you find a blog from someone whose opinion is so outrageous that you begin to wonder, who is this and who could they possibly attract? Leave it to Jeremy Blackburn who is an Assistant Professor in the Dept. of Computer Science at Binghamton University to find the answer. His specialty is, as he describes it, “large-scale measurement of socio-technical phenomenom. In a more, straight forward manner: I study jerks on the web.”

Blackburn has recently been awarded a five-year $517,484 grant from the National Science Foundation to devise ways to make online content easier to gather and sort, particularly from emerging social media platforms.

Charlene Weisler: What are the biggest challenges currently in gathering and analyzing online content generally and social media content specifically?

Jeremy Blackburn: The biggest challenge is keeping up with the explosion of features and platforms. While most people are familiar with Twitter and Facebook and maybe Reddit, there are numerous other platforms that have consistently arisen. E.g., Gab, Parler, etc. Other platforms have been around for years, e.g., 4chan and 8chan, but are specifically designed to be ephemeral and anonymous. So, there is a very real challenge just with respect to developing systems to collect all these different data sources. The next challenge is figuring out how to fit all these different platforms into a consistent and comparable framework. Not all sites have a "retweet" concept, some sites might mix concepts from other platforms, e.g., up/downvote and retweet features.

Weisler: Tell me about your multiplatform media dataset.

Blackburn: Most of our data is in JSON or archive HTML. We also collect multi-media (e.g., images), but the bulk (in terms of number of data points at least) is text. We have built systems to cover a variety of platforms over time. Probably the best way to get an idea of what kind of things we have going is to look at some of the data sets we have released: https://idrama.science/datasets/

Weisler: What is your sentiment rating system?

Blackburn: What we are working towards is a new formulation of the problem. For the most part, this problem domain has been thought about as looking at pieces of content in isolation. This leads to some consequences with respect to interpreting scores. At a high level, what does it mean for a piece of content exhibiting 0.01 more positive sentiment than another piece of content? Instead, we treat the problem as a competition between two pieces of content. E.g., which of these two pieces of content more positive sentiment? This seems pretty straight forward, but doing it this way allows us to borrow from rating systems that are very interpretable: match making systems. E.g., the Elo rating system that's used in chess. This opens up a ton of new opportunities because matchmaking systems are actually one of the largest deployed systems on the planet due to their use in online video games. These rating systems have a relatively simple interpretation. I.e., I can tell you precisely what it means if one piece of content has a 1800 positive sentiment score versus one that has a 1785 score.

Weisler: Can you delineate irony? Parody? Sarcasm?

Blackburn: These are interesting sub-problems, but, for the most part, they remain open challenges. One of the issues here is that these tend to be difficult problems for humans! This is really compounded when looking at social media where there is not just a loss of nuance, but also (pseudo)-anonymity, and cross-cultural differences.

Weisler: If measuring images, how do you handle memes? Do images include video?

Blackburn: We have a fair bit of work about memes. Here are some whitepapers describing our work.

https://arxiv.org/abs/2101.06535, https://arxiv.org/abs/1805.12512, https://arxiv.org/abs/2009.11792

Video is an area we are actively moving into, but I don't really have any results to share yet.

Weisler: How do you collect into communities for modeling? Are you able to build new segmentations?

Blackburn: There are a variety of ways that we group communities together. For example, we have used clustering based on the things that different users talk about, as well as the type of memes they post.

Weisler: Donald Trump recently de-platformed his blog. Do you have any insights into what happened and why?

Blackburn: I have done work on what happens when communities are de-platformed. E.g., we looked at what happened when Reddit's r/The_Donald and the incels community migrated to their own stand-alone platforms after being banned from Reddit. Here, we found that while there was definitely an effect on the communities, e.g., less membership, less overall content posted, that those that remained in the community became more engaged, and in some cases showed increasing signs of radicalization.

Weisler: How will you use what you have discovered to make the internet a safer, more honest space?

Blackburn: Beyond the obvious goals of helping the general public understand the modern Internet, there are more practical applications. For example, the techniques we are developing could help us identify mis- and dis-information campaigns in something approaching real time by looking for anomalous changes in behavior.

 

Facing the Challenge of Attribution. An Interview with Nielsen’s Matthew Krepsik

For many in marketing, deploying multi-touch attribution is more of an aspiration than a current reality, but that doesn’t mean we should defer efforts to find a complete attribution solution. There are many considerations when constructing a workable model, including variations in the consumer journey based on products and categories, the impact of unmeasurable factors like word of mouth and the ceaselessly expanding choice of datasets — some valuable and some, depending on the advertiser and category, not so much.

I had the opportunity to sit down with Matthew Krepsik, Global Head of Analytics for Nielsen to talk more about facing the challenge of attribution.

Charlene Weisler: Nielsen has always been proud that they own their data. Can you talk about the new reality where Nielsen will need to go beyond their own data and partner with other data suppliers who, in turn, control their own datasets?

Matthew Krepsik: From our point of view, we have a lot of unique and valuable data, just like other suppliers with walled gardens have incredibly valuable data. What we see as the biggest opportunity is our ability to co-mingle those data sets. If we think about our constituents and our users, whether marketers or  other business executives, what they really want is greater intelligence. We understand the complementary nature of all of these datasets and we can bring them together for specific use cases and help in enabling desired outcomes. This is where we generate the most value. As we think about the next generation of growth and innovation as a company, we think that the innovation stems from building across different partners. We have opened up access to our data with partners to make it easier to use and more permissible for marketers and brand owners across the value chain and in places where we don’t operate.

Weisler: How do you manage the de-duplication of data when you use other walled garden datasets?

Krepsik: There are a couple of dimensions of de-duplication around identity, around devices and around the cookie itself. So if you think about the ad model side, the ad tech really starts with the cookie. Your phone right now probably has more than 50 or 100 cookies on it. All of those cookies roll into a device. That device has to roll into other devices. So de-duplication is improving right now. Is it perfect? Not at all. But the first challenge is getting from cookies to devices and devices to people. I would say that we are getting more robust at the device level. The challenge is that they keep reinventing and updating the device. Every customer is getting a new phone. They are getting new laptops. They are getting new devices at home. Most households get new devices about every six months. So the challenge is that we have gone past the period of “build” and we have to constantly reinvest in the updating. The technology we have makes it easier to do this than ever before. The bigger challenge is de-duplicating your on-boarding data. That gives us a tremendous opportunity to get better at connecting to a digital consumer from an offline consumer. There is still a lot of work to do there.

Weisler: Looking at multi-touch attribution, where do you see it today, grading it from A to F?

Krepsik: I am going to answer this question along two dimensions. When I think about the overall need of a marketer or a CMO, I would give most attribution models a grade of D. If I think about the overall need for digital media planning, I think attribution models today are approaching a B+ / A- grade.

I say this because for a digital media manager, what you really want to know is whether this creative, or this site, or this device, or this placement working better than another one? Is this audience working better than another one? How do I make decisions and trade-offs across all of the possibilities out there? Today’s attribution models are really good at allowing digital owners to understand the cornucopia of media channels and how they can get more improvement out of them.

That being said, from an overall CMO standpoint, out of every revenue dollar that goes to the cash register, 25 cents is spent back on some form of marketing investment. Digital is only two cents of that quarter. So what they want to know is “should I be spending three cents on digital or should I be spending one cent on digital?” If you think about most attribution models today, they are not expressly measuring incrementality. They are not taking into account a lot of the “last mile” problems.

Weisler: Where do you see attribution going in the next couple of years?

Krepsik: Where I think the attribution industry has a chance to grow and where the marketing mix industry can take a step forward is bringing those two pieces together. Attribution models bring speed and granularity together and the marketing mix world offers scale and coverage. Where I see the industry going in the next two years is that both of those pieces come together; Leveraging the technology, real-time nature, and granularity in the attribution model with the scale, coverage, and sophistication of marketing mix modeling.

This article first appeared in www.MediaVillage.com

Not All Video Experiences are Created Equal. Recent Discovery Study Reveals Superiority of TV Platforms

Do consumers view and process ad content differently depending on the platform? Is television more engaging than other viewing platforms? Discovery thinks so, and to prove it commissioned a study on video perceptions with IPSOS that compared and contrasted viewer engagement, usage and intent by television and social platforms. The result proved that TV reigns supreme with engagement and intent.

“The study was designed to capture mindsets of consumers when using platforms, identify how advertising is enjoyed by platform and determine differences in the role and value consumers get from ads seen on different platforms,” explained Manu Singh, Group VP Commercial Insights & Digital, Discovery Communications. 

The highlights are as follows:

1. Different platforms have sharply different levels of engagement and personal intent. This is because of the way content is discovered. “Unlike videos on social platforms (which are most likely to be viewed as a result of scrolling or popping up in a viewers’ feed), viewers actively look forward to watching TV platforms, and say they are more personally invested, immersing themselves in content that engages and excites them,” noted Singh.

2. TV platforms (Live/Recorded/On-Demand and TV Everywhere)  have the highest level of intent Forty-five percent of TV viewers planned on watching on TV platforms, compared to only 7% of social media platforms.

3. TV Everywhere blends the best of both worlds with more appointment viewing and the ability to combine the access, flexibility and connection of social media.  The study showed that 26% of viewers are consuming TVE out of home – with 1 in 10 watching on their lunch break.  TVE viewership is spread across many platforms – from smartphone, TV and laptops through streaming, digital media players.  

4. The lower level of personal intent for social media was due to the way content is discovered – less by intent and more by happenstance. Social media video viewing was more commonly a result of video content appearing on a viewers’ feed or due to boredom.

5. Viewers are more excited about the anticipation on viewing programming on TV. The study found that 7 in 10 viewers said they look forward to watching content that is live / on-demand / on TV Everywhere. (TV Platforms 68% vs. social media 49%). And TV viewers are more invested in the content (68% for TV vs. 61% for social media).

6. TV platforms (31%) are considered more engaging than social media (23%) while social media viewers say they were less attentive (27% Social Media vs. 21% TV).

7. TV is generally a more relaxing experience for viewers and encourages greater engagement. Sixty percent of TV viewers report being relaxed while viewing content compared to under 40% on social. Oftentimes the reason for viewing content on social platforms is to overcome boredom but viewership on social platforms can also be stress-inducing or create distractions.
   
   

“So, for an advertiser who wants to really connect with the viewer,” added Singh, “Not all impressions are created equal. When it comes to delivering invested, engaged and excited audiences, we believe there’s no better platform - in all of its forms - than TV.”

This article first appeared in www.MediaVillage.com

Monetizing Celebrity. Interview with Wendy Dutwin

In a world of ROAS (Return on Ad Spend) the added value of the right personality and the right creative context now looms large. Wendy Dutwin, founder and head of Limelight Media, soon realized that there was a special role for her in celebrity procurement after years in production, both in television and in film. 

Celebrity procurement is essentially monetizing talent by matching them carefully to marketing campaigns. “We try to find the best opportunity with a client where a celebrity will have the most impact,” Dutwin explains. Many of Dutwin’s partnerships involve pharmaceutical campaigns where a celebrity can bring focused attention to the product or the disease. This poses unique challenges because of federal regulations and rules in the pharmaceutical area that may not exist in the consumer product and services sector.

Charlene Weisler: Does the celebrity have to suffer from the ailment in order to be a spokesperson for the product?

Wendy Dutwin:  Sometimes they do and sometimes they don’t. Blythe Danner was the spokesperson for Prolea, which is a post-menopausal medication. We needed a celebrity spokesperson who had those symptoms. But in the case of disease awareness campaigns, it is not as necessary for the celebrity spokesperson to have that disease.

Charlene Weisler: What type of research do you conduct to help match celebrities to products?

Wendy Dutwin: We know that there is a specific demographic that we need to reach. We tend to focus on women who watch a lot of television as the aspirational target. They may watch certain programs of TV and psychologically there would be an affinity or a message that relates to this targeted female viewer. Nothing intimidating. So in the case of Jennifer Aniston being the spokesperson for Shire’s Dry Eye Campaign, we sought a female celebrity who has the “look” and can relate to the target consumer.

Charlene Weisler: How can you tell if a campaign with a certain celebrity is successful?

Wendy Dutwin: Our clients have metrics to let them know that the chosen celebrity worked for the campaign. And there are a lot of marketing offshoots from certain celebrities. An example is Tim McGraw who talked about his campaign while as a guest on The View. It is not a transactional relationship – it has a more organic fit. So we focus in on the right person who can do the job well and who also matches the target demographic. We can build a campaign around the celebrity. We can also measure our own success by the renewal of the celebrity in the campaign by our clients and maybe even achieve a longer deal.  

Charlene Weisler: Is this usually a multi-platform effort?

Wendy Dutwin: Yes. We always like to build in a broadcast element and, with the divergence of TV, social media advertising is becoming a big part of what our clients want to do today.

Charlene Weisler: Has your decision-making on which celebrities to match with which clients changed since you first started?

Wendy Dutwin: We stay updated on the trends. Celebrities are now cultivated on different channels. YouTube is becoming a great source of cultivating talent. Our clients are always looking for the next big thing so we are in constant conversations with agents of talent. We have found that once the trend has hit the magazines, it has already exploded. We try to get in there earlier. We signed Adam Levine before he hit it big on The Voice and now we can ride the wave with Adam. We look for exciting partnerships and use our talent in more creative ways.

This article first appeared in www.Mediapost.com