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you my name is Marty Kaplan I’m the director of the Norman Lear center here at the Annenberg School if you don’t know about what the Lear Center is up to I invite you to Lear Center org to find out there are lots and lots of really exciting projects and one of them is is the reason that we’re here today the Lear Center is very interested in the impact of media on society and the question arises well how do we know if there is an impact on society or on individuals there and it’s certainly a field of study in communication but new technology is changing the resources to study these kinds of things and so we have now a new partnership with two foundations the Gates Foundation and the knight foundation to pursue these issues the project is called measuring media impact and engagement and we’re really excited about ramping it up and we’re going to be working with a lot of collaborators both here at the school across the university and I’m really across the world and as we do this work one of the things that we wanted to do was to bring here people who were real leaders in this area people who have been studied for example audiences or whatever we call the people who used to be known as the audience and one of them it’s our pleasure to have here today I’m excited both because of his work in the area of audiences which is you know sufficiently a rare thing to be able to find about in addition his work is his research is strategically chosen he does stuff that when you find things out that data can make difference in policy he testifies before Congress in the FCC he’s very interested in the policy implications and it affects the conversations we have about them and then in addition he’s also interested in I love this in the sociology and politics of the different communities that deal with this so that for example in the world of ratings there are people who work in advertising agencies and in networks all of whom are communities with their own habits in vested interests and to understand that as an aspect of doing the the number crunching and the the policy side that’s that’s a real triple threat his most recent book which I highly recommend in this area is called audience evolution and so please join me in welcoming the Fordham School of Business professor Phil Knapp Thank You Marty thank you everyone for having me here although I’m a sucker for anytime I can get a couple of days away from New Jersey in the winter so I’m really appreciative of this little reprieve my wife is very jealous but anyway yeah I’m gonna talk today this is the the sort of the lengthy title of my talk audiences consumers audiences citizens new tools for measuring media engagement and social impact and it’s Marty mentioned he as he told me a few weeks back about this project that was ramping up here and it got me very interested because it does really intersect with a lot of what I’ve been doing over the years I’m just gonna talk a little bit about that first to sort of sort of contextualise a bit sort of the perspective I bring on some of this first as you mentioned I’ve been doing some work on on audiences and really how long with the notion of what we call the institutionalized audience that is how do different institutions make sense of and conceptualize the audience don’t laugh at those time at those covers by the way I saw someone snickering my publisher clearly hates me and but the worst part was this was the first horrible one and my wife designed a great one for the second book and they said no we don’t want to have inconsistency in the design so we need two crappy covers so anyway just kind of like I go I think I’m still better but

anyway so so yes so and there are a lot of these issues of measurement and how information and data about audiences are used in decision-making is something that’s interest to me quite a bit but I’ve also been working in the policy space on unrelated in some ways measurement issues I hope the way that these are related will become clear in a moment so for example some of you may remember a number of years back the FCC went down this path of trying to develop what they call the diversity index a way of trying to measure the diversity of media markets that could inform and guide in particular media ownership policymaking and and and that was actually a byproduct of some work a lot of us were doing in this in this space in years before that and it went in some directions that a lot of us were not particularly happy about certain a few years back I worked with an organization called the Center for American Progress to try to develop some alternative approaches really convening actually the same sort of this what you’re doing Marty sort of a group of people from all sorts of disparate backgrounds to try to come up with a viable alternative that it turned out not only did nobody like it which made me think maybe it’s actually good because whether you were a for or against immediate consolidation you didn’t seem to like it you know where our measurements were going but more important it actually got us got me and particularly interested in a related issues because part of what made this so difficult was the issue of obtaining and gaining access to the wide range of relevant commercial data sources that are essential to to doing this kind of work and not only it wasn’t something that only we ran it was even something that the FCC itself was running into gaining access to data that they knew was out there but gaining the kind of access necessary to really construct these robust portraits of media markets and essentially the functioning of individual media systems so that led me down a pathway that I ended up working with an organization called the Social Science Research Council on a program called necessary knowledge for a democratic public sphere and as a title suggests a big part of that was about trying to better inject the kind of data and information and research that could inform policymaking that could impact of the structure and performance of our of our public sphere so all these things sort of get tied right into in many ways I think these issues of media engagement and social impact because all them in different ways we’re trying to you know are providing potential tools to get at this interesting challenge which is how do we effectively evaluate different kinds of media in enterprises in terms of whether or not they are having a particular social impact are they engaging audiences communities users whatever the terminology we decide is most appropriate so and to ground this also there is a sort of and I won’t get into it too much detail this sort of law or their large and interesting body of literature on this notion of the audience as citizen versus the audience as consumer and a lot of it has been you know targeted at this in this realm of policymaking and what does policymaking look like if it considers audiences more broadly beyond the notion of consumers of media and really thinks of them as citizens as publics etc and so I’m gonna try to distill some of that literature down into some basic components and I don’t know if I hit on all of them I’m sure folks here might be able to even chime in with additional dimensions of this but at the most basic level it does mean going beyond exposure am I’m going to talk about this notion of exposure a bit today and how it you know contrast with some of the other ways we might think about audiences or citizens for that matter but beyond that notion of sort of a passive exposure to content which can include for example going beyond exposure could mean the extent to which an audience is cultural and informational needs and interests are being met the other part of what I’ve been working on as of late that I didn’t mention before I actually collaborated with with with the Annenberg School on this was some work that came out of the knight commission’s report on the information needs of communities the FCC decided they wanted a wide-ranging literature review on how community information needs are should be defined and how they are being met by you know by by our media system and that was a project we did last year is touching on here still she’s still student has she gone kochak I work with CACCI I worked with Ernie and and as is the often the case in the realm of doing policy research and landed on the FCC’s desk so they said thank you very much and absolutely nothing has happened since but you know we worked hard on it but anyway second the issues of the many roles of the audience in the media ecosystem and I’m just a couple of these here sharer as participants as producer etc again taking us beyond the notion of audiences as consumers and then of course into the wide-ranging realm of potentially

relevant effects that content might might have so these you know these are some some basic elements of what we mean when we really start trying to move beyond the notion of the audience as consumer but in fact a lot of what I’m going to talk about today is derived from the work I’ve been doing as of late in the audience measurements space which has that you know historically needless to say really oriented itself around that basic notion of audiences consumer and one of the things we’ve been talking about trying to understand within the context of this larger project is how some of that might be essentially repurposed to address broader issues that we you know reflect you know notions of the audience a citizen and how information needs an impact etc could be considered so anyway as a starting point and this comes from the from from the audience evolution book I think it’s useful to think about us today as being in in the commercial space what I call a post exposure audience marketplace where exposure has a much more limited value are much more limited influence in terms of his role as a as a currency so to speak and as being but but remains as this is meant to illustrate really does remain at the court does not go away it’s not irrelevant because it is indeed the the starting point for a lot of these other concepts which as we’re going to talk about are starting to gain traction as alternative sources of a value so to speak and when I use that term value again I’m gonna be talking about it primarily within the context of of advertising supported media but you know within this project I think what’s interesting is that we can sort of think about that notion of value and so many other broader richer more you know politically resonant socially resonant ways what I try to do is model you know essentially oh and this is sort of meant to be sort of a process the the the dimensions of being a member of an audience ranging from the earliest stages of awareness about content through which then in theory can potentially translate into interest which then can lead to exposure and then it gets complicated again I I tried to put these in some sort of sequential way I put two concepts there attentiveness and loyalty as sort of offshoots of this notion of exposure because if you look in the in the in the measurement space essentially measures of attentiveness that is how often how much are paying attention or loyalty that is how frequently do you consume some kind of media content are typically derived from exposure measures that are that are being captured so attentiveness might really often be just simply how much time do you spend consuming and how much time which how much exposure do you have and loyalty would be the frequency how often do you go back to it but then we get beyond that and potentially we get to the level of we reach appreciation and emotional response couldn’t fit that Hallel in the box there and then possibly recall an attitude change then ultimately some kind of behavioral response now as you’ll see there I have this sort of umbrella term engagement which I know came up today as well and and we’re gonna try to tackle a little bit today but what I tried to do there was essentially map what I was seeing in my research at the time were all of the ways all of the multitude of ways in which various entities in the media space whether is advertisers or content providers or measurement firms were operationalizing this notion of engagement and it’s included one or all of all of these things so it can even include some dimensions of basic exposure like attentiveness or loyalty in the online space you know there will be of course you know something like stickiness is often taken as a as an engagement measure in and of itself or appreciation doesn’t going to talk today about some of these social media analytics and emotional response or things that can be captured and considered it part of engagement as well and then of course recall an attitude change and then even of course various types of behavioral responses which can range from anything from of course in the realm of product purchasing behaviors but perhaps to sharing activities or social media activity etc but so I don’t have a I know coz that questions gonna come what’s an engagement mean I this was not meant to answer that it was just meant to map what the the the the media sector was was was including within their various notions of engagement but in this you know in this sort of post-exposure audience marketplace what’s interesting is that whereas the value is all traditionally lied there there are a number of forces at work that are making that no longer viable that is that that can be or should be the only source of value and I think for all of us who probably think that everyone should be thinking about audience is in a more sophisticated way this is sort of a promising and an exciting thing so what I’ve tried to do

here is sort of describe you what I see as these opposing forces in the in terms of this realm of audience measurement and valuation the things that are moving us beyond exposure this will become clear a bit what I mean by audience dark-matter this idea that there is all sorts of audience attention audience exposure out there that in the contemporary media environment no longer can be effectively captured by the existing measurement systems I think it’s the one thing I remembered from my freshman astronomy class what dark matter was it’s that stuff that we know is there but we can’t actually you know quantify it effectively interactivity creating and I’ll elaborate all those in separate slides in a minute but these are some particular things that provide not only the necessity to move beyond exposure but also tools to facilitate that and one of the arguments I make it audience evolution is that we can own this this kind of thing can only happen when there is both the opportunity and also a sufficient challenge to the status quo from an economic standpoint we were talking yesterday about for example in the 1980s there was an effort to fund a alternative system to the Nielsen ratings called television audience assessment and it was the idea was that it could actually measure not only exposure but appreciation and demonstrate a linkage between appreciation for the programming and and product purchasing behaviors and things of that sort if I remember the details correctly and the problem was and Marty asked the question why did it fail and the answer is very simple it was a solution to something that no one thought was a problem yet now this is a no because the status quo was working just fine and maybe that would have been better but you need massive disruption for the to the status quo and that’s certainly what we’ve seen as of late in this environment of extreme fragmentation where it’s becoming more and more difficult to rely purely on the monetization so to speak of exposure that to save the people of a band that these in various institutions have abandoned that model by any stretch of the imagination so we have a variety of efforts ongoing ranging from things as simple as increasing sample sizes to fit to traditional sample based measurement systems panel based measurement systems – we see in the online space realm of hybrid measurement where you you you meld panel data with server log data as a way to try to compensate for the inability to generate and maintain samples that are sufficiently large to capture the distribution of audience attention online – what we’re seeing you know getting to this issue of fragmentation across platforms or the cross-platform campaign ratings that the Nielsen Company has recently rolled out that can actually give you a rating for a television program for example across online and traditional television platforms and then the recent announcement by arbitron and comScore of a 5 platform measurement system but again the reason I put these here is because they all are still operating under that basic notion of trying to maintain an effective way of measuring audiences exposure so their innovations in many ways but in it at that core level they really still are about capturing exposure and nothing else and with the idea that that would continue to serve as the primary source of audience value now so getting into what I mean by dark back just some examples and and and and some of these might be you might find eye-opening I know I did as I learned about this as much as 50 percent of television viewing is on unmeasured platforms and so there is that constant catch-up that measurement systems need to to be involved in of course now it’s it’s mobile devices and tablets in particular that are that the measurement folks are trying to effectively capture and to put this into more concrete sense Nielsen reports ratings for approximately 80 of the over 500 television networks that are in operation so over 400 television networks do not have ratings their audiences are too small now the interesting thing is though is that only accounts were that those 420 here so well combined will they account for about 20 five percent of television viewing but nonetheless roughly 25 percent of our total exposure to television program is on what we would call unmeasured networks and basically only the top 102 programs have the full scope of detailed ratings that that meals and can provide go into the radio space even radio old medium only about half of the over 13,000 u.s. radio stations have ratings reports from Arbitron most of them are in are in areas that they follow their later don’t even consider worth trying to measure in them in the magazine space MRI measures readership of 232 of over 5,000 magazines and if you look online and you know I pulled this number from somewhere god knows of 180 million is anywhere close to the accurate number of websites and operation but the bottom line is even by the current systems it’s

about a hundred thousand websites that can be effectively measured even via these hybrid panel sample-based panel and server log systems by by the you know the the predominant measurement firms so that’s what IV by Dark Matter lots of it now then in terms of on the other side where the drivers towards looking in different directions the traditional model is of course this we’re basically audience exposure is what the content provider learns about but in this increasingly interactive media space everything ranging from search activities to appreciation to participation to production and response all of that can be captured via the ways that we in which we can engage with media in in so many more interactive ways and I’m gonna boil that down in particular it is one in particular platform in a few minutes but just to give you an example there are now going back to that model before all sorts of organizations that are looking to capture different dimensions of that of the of that model what ranging from awareness and interest to engagement and recall has anyone ever played gone to WWE are award TV comm anyone familiar with that example I use with my students it’s upside that you go to and it will ask me to take part in quizzes about TV shows and you’ll see how many you can get right and the more questions about tonight last night’s episode you get right you can win points that you can redeem to potentially win prizes etc and is actually part of a Nielsen measurement system designed to measure our recall of the programs that we watch and that’s their measure of engagement they call that engagement so if you can remove you can answer ten questions correctly about the show maybe even about some of the commercials that aired during the show that’s an engagement metric that indeed some networks are using as part of their providing make goods and guarantees just like the traditional model has been well we don’t deliver this audience we will provide make goods and give you credits towards the difference some networks have entered into contracts where they’re using that very basic and again some of your pricing that is not engagement engagement is a much more complex it must be a much more complex phenomenon then can you answer ten questions about last night’s television show correctly but yet you know that that has gained traction in the marketplace tells to me it’s very telling that that is the amount of sort of disruption at work here the willingness to essentially grasp on to all sorts of alternatives that might prove to be to be viable in cadiz you’re probably asking that I know there’s a mixed audience here but the the you know the social scientist and they were saying who would actually go and do this and how could they possibly be representative of the population as a whole who would bother to go and play reward tv.com and how can that be possibly representative of the television audience as a whole and that raises all sorts of other issues that fascinate me these days where it just seems that the quantity of the data you could gather is increasingly capable of outweighing questions about quality and and and that’s that’s sort of to me one of those sort of we’re talking about big data before with Ernie that sort of the larger I think philosophical question that arises as we start thinking about some of these issues emotional response companies that do that as well the Q score folks have you know there’s a still work in that area behavioral responses so any of those spots on the chain now there are measurement organizations trying to quantify it in ways that can make it potentially monetizable for for content providers as I say it’s a quiet number of different types of hammers out there looking for nails that is theirs you know they there are these tools that are being developed and we were talking before now I mean forget name there’s a company I wonder I had a conversation with the executive at a company called nano crowd and this is a good example this is a company that has essentially developed a way of determining what movie you’ll people will like based on the words they use to describe films that they have seen so it’s not about you know so it’s not the Netflix model of how many stars you give it but it’s just scraping the social media and blogosphere space for the words that are most frequently associated with certain films to describe them and do those words appear in the descriptions of other types of films and apparently it’s a very good predictive tool for the old if you like this you’ll also like that and literally it turned out that this the folks in this company we’re just looking around trying to find out what market there might be for this they developed it probably for some other reason entirely but with no particular solution to a particular problem in mind or at least not this one but they’re just looking for possible applications for this and that’s what’s interesting about this space now is there are there are applications that are being used or the way of trying to figure out ways that they could be applied that they weren’t necessarily originally designed for and so you know that’s that’s I you know I think this analogy is is relevant here the other thing that’s important I think to understand this current space right now is how often on the consumer end and I found this in some research

I’ve done more recently for Time Warner when I’ve gone out and I’ve been asking in particular various types of content providers whether in the television space and in different media spaces you know understanding how they behave and what they’re thinking as consumers and users of all these different kinds of audience information systems and the the theme that emerged over and over again was they emphasized that there they see themselves as researchers even in the business of needing to tell compelling stories so some representative quotes I must have heard this exact same thing told to me by four or five different people if we don’t have the ratings story to tell we have to talk about audience quality and so again the idea is is a fewer and fewer of the content options out there have a rating and by a rating story to tell we really mean exposure story to tell and we can’t we can’t essentially get you know capture sufficient value from our audience purely on the basis of their size which is really what exposure emphasizes or we increasingly we hear discussion within the space of the rating story versus the engagement story and so if we don’t have a rating story to tell we want to be able to have an engagement story to tell now again from a social science standpoint you start hearing about data and storytelling and you know you you start to get a little nervous but you know I think this is also the reality of the audience marketplace what’s interesting then in this environment that we see now where we are looking beyond exposure where that all these institutions are looking beyond exposure to alternative sources of audience value is that it actually takes us back to some of the early days of audience research in this country a couple quotes from from well-known researchers in our fields I’m really founding fathers in many ways here’s one the first one and these go back to radio we have lost sight of our primary purpose for measuring radio programs we really want to know is not how many persons are listening the real information we desire is how much influence the program in question is exerting now in this case it’s on sales but this is the again with this project what’s interesting is we could take these questions and go well beyond issues of sales which not really all that interesting or but again you look at paul lazarsfeld who was really one of the pioneers in terms of true academic industry partnerships in the early days of audience research and the radio space even worked in the realm of motion picture research a bit and basically he saw that entire industry move in the direction that he was he didn’t expect to go and and certainly his early research wasn’t wasn’t focused on as he’s he mentioned a questions of preference of radio research have been almost discarded in favor of actual listening figures that this is not necessarily the best solution and maybe just as important to know that a person likes a certain program all that early research that came out of the radio Research Bureau really looked at a wider variety of dimensions about you know involving the relationship between radio and its audience and yet the way that that that industry developed was one in which all that sort fell by the wayside and the focus was on the much more narrow issue of what is that size of that audience and note at this point in time we’re not even gotten to issues of composition yet we’re not even at the point later really more in the 1980s where that second major transition took place and it was about the demographics of who was exposed this is just this is just the raw the raw numbers era but now we are in many ways you know circling back and you know and have both the tools and the incentive to understand audiences in more robust ways and so in particular I want to talk a bit about some research I’ve been doing on social media analytics in particular in this case I’ve been focusing on the role that social media is playing in the realm of the television not surprisingly many of the social media analytics providers have been focusing on the television industry trying to gain traction there as an alternative or supplementary currency so to speak not surprise it because that’s where the largest amount of ad dollars really are so here’s some examples from the trade press if you know this which I was thing that struck me is there is this incredible sort of excitement or you know enthusiasm for this notion that there’s a massive transition taking place the idea that it would actually become a replacement for traditional Nielsen ratings is very interesting the reality is of course somewhat different you guys all talk about it encountered a lot of skepticism amongst the users of this stuff and there’s with good reason to some of the data i’ll show you will indicate but it’s an incredibly at this point in time incredibly crowded space that’s changing day to day some of you may have heard for example one of the major providers in this area bluefin was just purchased by Twitter social guide was just purchased by Nielsen so there’s all these providers of social media based audience information out there and probably a lot of you are familiar the basic process is sort of algorithmically

driven web scraping of a defined set of platforms and the appropriate words are associated with the appropriate programs and essentially top 10 and top 25 lists can be produced just like with traditional Nielsen data what are the most talked about shows online what are the most liked shows that can be that can be accomplished and they claim that is being able to identify sentiment associated with the words that are being used so this is this is the space that I started looking into a bit more deeply for that for the time warner project and it’s interesting of course because big picture wise if we start to project ahead to an environment where indeed this sort of social media activity becomes the key driver of cultural production there’s you know all sorts of changes that could result you know we are certainly are talking about a model where we instantly have a greater diversity of success criteria that is if you could succeed by the traditional exposures story or you could succeed via the social media engagement story then suddenly that creates more opportunities a couple of different criteria by which content can potentially be economically viable here’s a quote from one of the my interview subjects for the project lots of people are trying to show lots of different types of success so there’s the potential that this really can unlock untapped sources of audience value and could indeed promote greater diversity of content on the other hand and I stole this from that old chestnut from the Alire Center from Europe’s back more or less tyranny of the 18 to 49s that is it’s possible there’s some data that suggests that this exact same demographic that has been overvalued by advertisers for so long if it turns out that they’re exactly the same people who just are constantly on Twitter talking about television programs then this could reinforce that or create some other very narrow demographic grouping that develops disproportionate influence in this space so maybe the tyranny of tweeters is what we are looking to on the horizon and but in the end result would be the potential for the overvaluing and that’s the creation of content for this very active minority that is again not necessarily representative of the population as a whole so these are some of the bigger picture issues that arise in in this particular direction that the measurement of audiences is evolving in but one of the things that came out of this work was an opportunity to work directly with a large media buying agency in New York who had turned out shared my interest in this and wanted to do some comparative analysis so this is sort of a real basic question they just wanted to know you know there what were the differences between some of the leading providers these data for me what was interesting is the big is the bigger picture of you know what at what stage in this evolution of these kind of audience information systems are we at in terms of whether or not these things are giving us any kind of consistent portrait of the media audience so they were able to obtain from you a small amount of data to do sort of a pilot analysis of a one-week time period again three three services provided us with data we analyzed primetime regularly scheduled programming our unit of analysis was the individual program rather than the individual telecast and that gets important as we learned because my god and I wasn’t hanging out my room last night diners drive-ins and dives just keeps running one after the other after the other I mean some shows literally will air 20 times 30 times in a given week on a network so if you if you have the individual telecast the unit of analysis it complicates things because there’s a lot of variety there so we were actually it’s the entire program no matter how many times it ran that was our unit of analysis and so we were able to obtain data not only on the volume but on the valence and that is you know not only how many people mention a particular program but how much they in theory liked it or didn’t like it and these these services issue rankings reports just like traditional Nielsen rankings reports on the basis of these criteria and then we were also able to obtain Nielsen data it’s just as a basis for comparison to see what the portrait of the television audience looks like via old versus new measurement systems just to give you a sense so this was a and this is you know very very basic it would be fun to get a hold of a lot more data and do some more sophisticated things but I was just thrilled that they were willing to let us do this with their data and especially because then we were we provided this presentation to the American Association of advertising agencies to the council for research actually excellent so we were able to sort they were they were comfortable with letting us present these findings to a lot of different industry associations that were essentially pondering roll this should play in their in their day-to-day work but if you look so for example the percentage is essentially the percentage of overlap how many within the top 25 programs appear on both lists and this is you know and so placement is a whole nother issue this is just are they are there commonalities

in their top 25 and if you go across that first row you see for example between bluefin and general sentiment and Trender these are three of the major providers in this area you’ve got 40% agreement that level of agreement drops when you get to Nielsen measures both at the household level in the 12 to 34 level and then the next row you see wealth so really essentially the services all agree with each other in about the 30 to 40 you know 35 to 40 percent range lower levels of agreement in general with with the Nielsen data not surprising but to me this is where things get particularly interesting if we then you change the unit of analysis to the sentiment zeroes so now again what what does this tell us is essentially tells us even these numbers I think these are relatively low levels of agreement because we have to remember this too and I have different I didn’t put the the graphs where I tried to graph out the in a more sophisticated way but these are the top 25 programs so if there’s going to be anywhere where you only see a green when you when you look at measurement systems generally the pattern is the the agreement amongst the most popular content options is higher and then it tails off so if even within the top 25 the agreement level levels are this low and indeed we saw this we saw this that they didn’t necessarily even agree on the number one program or the number two program so at those very basic levels these are fundamentally different and if you if you looked at the actual raw data what you’re able to look out as well you know what you know a program that was number one for the week and the bluefin data had 300,000 or so mentions and a program that was number one in the trend or data had 1.2 million mentions so what and that just illustrates massive methodological differences between these conceived mechanism they’d all sort of claim they’re doing the same thing but they’re doing it in such very different ways that they’re providing portraits of the audience that to me have very little commonality with each other it’s not like the old days of you know when Nielsen and Arbitron were both doing TV and you’d see 10 12 % differences these are these are massive differences in in in what they’re what they’re showing because so the differences that you’re seeing into these numbers in this case of volume is literally in the kind of that account of you know how they take the raw content turn that into a mention and the counter dimensions know this number is just the list in that you percent overlap in the list and I mean underneath that that the list is based on following love right right right so the the reason for the difference in these lists is the way they calculate whether either the way they calculate exactly and these differences can range from the time period that they sample from the range of platforms that they use some focus almost exclusively on Twitter and and public Facebook some incorporate the blogosphere in addition to what somebody may be using some of these TV check-in platform services like get glue and things like that that that data get fed in some actually even gather news data from from from news websites so there’s all sorts of ways that you could approach this and what was important whatever is entering for me was what essentially from the standpoint of saying you know the advertising industry that they realize this is a space that’s highly fragmented in and of itself right now different methodological approaches producing vastly different results and so they’re then faced with this challenge of figuring out and now and of course you would like to say well let’s figure out which of these is most methodologically sound and but that was the other issue we found with this study that there are very significant methodological details that are all being kept proprietary at this point not surprising given how competitive this space is so that challenge of sort of digging underneath the hood and really figuring out which of these folks is doing it well is something that it’s tricky but anyway well we you know I you know it’s in some ways some of these numbers that sort of you know in this particular case is a glass half-full glass half-empty a might be open to interpretation but in these when you see this incredibly low levels of agreement sort of what counts for like not liking a program his meaning entirely different things across these different providers so sir that was again sort of a bit of a tangent in some ways but to the larger question but I thought it was interesting just from the standpoint of understanding sort of where this space is in its evolution right now a lot and so what I see going forward though in terms of how these issues can then be addressed from the standpoint of the purpose of this project which is really about trying to evaluate the impact of all different kinds of media you know not just commercial media but non commercial media efforts as well one that comes up is how might these various sort of commercial measurement systems potentially be repurposed for alternative uses to get beyond answering the questions that perhaps advertisers care about but to the questions that

foundations might care about or grantees might care about when it comes to evaluating the success or failure of their work as I mentioned the other one I call this notion of the black box audiences how you know can you really confidently use any of these systems for understanding audiences if there is this little transparency about how they’re constructed but in turn on the opportunity side I think we are really at a bonafide historical moment where not unlike what we saw in the 1930s when there was that need for a genuine academic industry collaboration to try to understand the nature of the audience that was what you know that radio created I think we are at this very similar point right now where there is this opportunity for those of us who do research in this area to really potentially contribute to the first substantial redefinition of audience value in 30 years and I say 30 years cuz I put the last sort of major transition back to when we really moved into focusing very explicitly on on demographics you know prior to that that was more just raw circulation figures were all you know viewership figures without parsing out the audience in a demographic way and then lastly develop mechanisms to support diversity of content providers that I think that is something that ultimately could emerge from this space if indeed there is acceptance of a sort of institutionalization of a broader array of criteria for success and there seems to be you know sufficient demand on for alternative ways of valuing audiences and I think that’s that’s something that we’re likely to see in this it would be nice thing for those of us who do research in this area to sort of make even a stronger contribution to that to that process so thank you I’m happy to answer any questions yes when you talk about audience exposure and I presume you’re talking about audience exposure to the sexual content so like the the initial show or program but then what about the audience’s exposure to ancillary content that comes out of that you know either people that do remixes of songs or people that do re edits of TV shows or they share you know whatever and then is there any way to measure that and then and how that might bring those people back to the original content because that’s that’s where I in terms of the research that the the industry sector is doing right now that’s what they’re trying to understand first and foremost and where I find it interesting bout that is essentially yes how do all these more robust ways that audience is engaged with content well I find frustrating is what they want to know is to what extent does that drive them back to the basic thing the core the simplistic notion of how many people watched or read or listened and and so you know I think there are so many other interesting questions to answer these kind of data other than does you know social media activity Goose ratings which is really if you know all you see every couple of weeks in the trade press is another study of that oh it’s a 1.2 percent in the 18 to 49s that you know and so if you’ve already noticed there’s no doubt that television programs are working hard to try to you know boost their social media activity you know hashtags at the bottom of the screen or you know as what happened was there was at the Grammys when Jimmy Kimmel told us all to to tweet that Tracy Morgan had passed out on stage you know but there’s there essentially it becomes a a mechanism to try to drive that that traditional metric but you know so that I mean that’s that’s my take on the role that that’s playing now it seems like there will always be pressure for exposure to be the primary measure of effectiveness because that is the broadest level at which things happen since we still don’t know very well how you get from exposure all the way to the end point of buying and endorsing a product will always be sort of pushing towards exposure well that’s the thing is every time you move further down the chain your lopping off opportunities to monetize people I mean even at you know I mean it’s already happened in the exposure space and the television arena some of you may know where the system now that works is the c3 rating so it’s only commercial viewers that get monetized now and if so

if you’re watching the show and not watching the commercials you’re no longer being monetized and so you know the more you the further along the process you go the more exposures you’re no longer essentially monetizing this is an incredible exactly this incredible institutionalized incentive to maintain exposure that’s why I maintain it as the core but the counter force to that is that there are so many in this highly fragmented media environment content providers for whom exposure does not represent a sufficient way to capture revenue to support themselves but of course for that to work there also there needs to be advertisers and advertising dollars out there that are willing to look beyond exposure so that complex interaction is ongoing and and there and there are that advertisers I mean because once again is you know no one is you know there’s not a massive you know you

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