Culture Design 101

Culture Design 101An Introduction to Our Meme Research Methodology

Prepared by:B. Lazlo Karafiath, Producer Joe Brewer, Research Director+1 415 603 9506 +1 206 914 [email protected] [email protected]

Culture Design 101 - An Introduction to Our Meme Research Methodology

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Mapping Out the Next Generation of Cultural ResearchCulture2 Inc. and its collaborators have pioneered a methodology for mapping ecosystems of ideas that reveal how and why they spread from one person to another. In this brief, we share our general approach to provide greater clarity into the emerging best practices of cultural research.

Limitations of Standard ApproachesMost cultural research—whether it focuses on consumer behavior or organizational practice—is conducted through the use of polling, focus groups, and structured interviews. It is typically divided into qualitative or quantitative categories, implying that a trade-off must always exist between interpretive nuance and numerical rigor. And research is usually approached through the theoretical lens of the researcher, whose selection of language tends to frame the study in a manner that is consistent with prior research using the same technique.

All of these factors introduce constraints on the value of cultural research. Subjects are asked to declare how they think and feel when responding to opinion polls, despite a mountain of psychological research telling us that what people say is a poor predictor for what they ultimately do. Clients are restricted to qualitative or quantitative analyses even though combined approaches can now provide the best of both worlds without significant increase in cost. And the influence of ‘priming effects’ in the framing of language is well known as a source of bias in the interpretation of results. For all these reasons, the standard approaches are insufficient for analyzing and influencing cultural systems.

The False Choice of Qual vs. QuantDifferences between qualitative and quantitative research are well known among practitioners. What is not well known is the fact that they were never truly separate. Many subjective evaluations go into the selection of a numerical technique, with the result being that a quantitative measure is only as good as the interpretive framework in which it was


developed. In other words, you can always get a number but it it may not actually mean anything. For example, a study that claims “64% of respondents are concerned about the environment” will have the feel of being concrete. But what does this really mean? The use of a numerical metric makes the finding seem more robust than it actually is.

Similarly, there is a widespread misconception that interpretation cannot be done with rigor. Indeed the hallmark of a well-trained qualitative researcher is their ability to analyze and evaluate information with clarity and accuracy. This goes beyond the superficial, where a finding about medical health might show that respondents “have a positive impression” of a new drug on the market. Researchers can now analyze the rich semantic structure of language to show how the worldview of a group of people is organized around particular understandings and value priorities. If they are educated in cognitive anthropology or social psychology, they can reveal the motivations that drive behavior by deconstructing the social contexts where decisions are made. This is how usability design and information architecture are done on websites, in urban planning, and other application spaces where qualitative methods have matured considerably in recent decades.

For too long there has been a false choice between qualitative and quantitative methods. One that both obscures these nuances and their implications for robust research while also concealing the fact that a middle way is possible (and in many cases preferable) to one or the other approach.

Beyond the Problem of Researcher BiasTwo major issues plague the domain of cultural research. The first is a misguided notion that people know their own minds. The second is the presumption that researchers have an unbiased “god’s eye view” when they design a study. When a poll is conducted, the presumption is that a person simply needs to be asked how they feel (or what they will do) and their answer is a reliable predictor of future actions. This is a bias that may be held by


the client, the researcher, or any stakeholder who interprets the findings from a cultural study.

Similarly, when a researcher creates a survey or designs questions for a focus group, the subtle complexities of language are often not fully recognized. They may be aware that word choice will influence the outcome, often in profound ways. But if the researcher has not been thoroughly trained in cognitive linguistics (which few are), they are unlikely to have the advanced technical skills to map out the semantic feedbacks associated with the neural processing of language. This is akin to the enthusiast who has read popular science books about theoretical physics but lacks the years of formal training of a Ph.D. physicist working in a research laboratory. Linguistic analysis is highly technical and requires years of study to achieve mastery.

The researcher may be well educated in a particular approach—conducting opinion polls, moderating focus groups, or some other specialized technique—and is often brought in by the client to apply this particular skill. As such, they will tend to construct language that draws from and reinforces the perspective underlying their approach. But many researchers lack formal experience with the deeper philosophical considerations that inform the design of research tools. In other words, most researchers are trained as technicians rather than as scientists. So they may be skilled at their technique but lack the depth and rigor of critical assessment that would come from the experimental process of creating and improving a research technique. As a result many researchers default into habitual selection of language for their studies without a full appreciation of the way this introduces bias into their methodology.

Getting around these issues is easier than it may seem. All that one needs to do is monitor and observe people’s thoughts and actions “in the wild” without prompts from the researcher. If you want to know how people talk about your product, you can simply observe them talking about it in their natural settings. You don’t need to create a survey


that requires them to react to your choice of words. Qualitative researchers with good ethnography skills know how to interpret what they see as observer analysts. This skill set applies here as well.

Toward A Science of Cultural DesignWhen all of these issues are addressed, a new approach to cultural research becomes apparent. The framework from which our methodology was developed takes them into account:

✦ Combine qualitative and quantitative methods to introduce numerical rigor while ensuring that interpretation is done well.

✦ Observe behavior in the wild to avoid measuring reactions to researcher language and thus get a more accurate reflection of the real cultural drivers.

✦ Create scientifically testable models that explain why people are behaving as observed with accuracy, clarity, and testability.

At Culture2 Inc. we have developed a methodological approach that overcomes important limitations in the field. We now offer research services that deploy this approach for the design of cultural change.


Overview of Our MethodologyIn this section we present the steps involved in conducting viable research on cultural ecosystems. A central concept we apply is the meme, which can be thought of as any unit of cultural meaning that spreads from one person to the next. A meme can be any story, idea, or practice that is replicated by others. One example is the practice of rubbing two sticks together to start a fire. When one person in a society figures out how to do this it can quickly spread to every other member of the group. Another example is the idea that growth is good which has guided economic policy for decades in the Western world. Memes like these propagate across social networks and compete for attention in the minds of people around the world.

In the discussion that follows, we will explain step-by-step how we conduct our research. To assist in making each step more clear we will provide a case study from one of our projects completed in the fall of 2012 where we mapped the meme landscape for the Coca-Cola brand using Twitter data.

Step 1 - Harvesting MemesThe first step in our research is to gather memes that will be analyzed for rich semantic content. We harvest memes in three primary ways:

1. Conducting Memetic Interviews: Identify thought leaders and influencers of culture. Use an open-ended interview process to get them talking about the topic under study. Write down what they say verbatim to capture the unique manner in which their mind constructs their thoughts. Enter these verbatim statements into a meme database.

2. Data Mining on Social Media: Use keyword and hash tag searching to gather tweets on Twitter, status updates on Facebook, comments on blog posts, etc. Enter the text verbatim into our meme database.

3. Facilitated Meme Hackathons: Organize a social event where influencers of culture are brought together to discuss the topic under study. Have them get into


small groups and talk. Gather memes by having participants write down verbatim the statements of their peers and tweet them with a specialized hashtag for later data capture.

Step 2 - Sorting and Grading MemesWe can now begin to “preprocess” the data and prepare it for analysis. This involves the standard clean-up procedures to ensure data quality, followed by a specialized protocol for grading the semantic content of each meme that assigns a numerical value while preserving qualitative information.

The sequence goes like this:

1. Clean up the database by removing duplicates and restructuring the data so an analyst can easily go through and assign numerical values.

2. Introduce a taxonomy of semantic filters that will be used to grade each meme. Each filter is a set of binary opposite words (such as Up/Down or Male/Female) that represents an emotional tension deemed relevant for study by the analyst.

3. For each meme in the database, assign one numerical value for each semantic filter that reflects both (1) its relevance for that meme and (2) which polarity it aligns with most closely.

Case Study - Harvesting Memes About Coca-Cola

In this study we limited ourselves to social media. During a one month period, we downloaded all tweets on Twitter that mentioned Coca-Cola and were retweeted at least once (an indicator of replication). More than 5000 unique memes were gathered in this manner.


4. This procedure is used to create a large matrix of numbers that will be used in the statistical analysis described in the next section.

Step 3 - Number Crunching to Reveal Statistical PatternsWe are now ready to apply factor analysis to the numerical data for our meme set. Factor analysis is a well-known statistical technique for identifying how diverse factors vary together. In our case, the factors are both the memes themselves and the thematic tensions of our binary semantic filters.

The most important output of this statistical analysis is the “clustering of variance” that tells us which thematic tensions are most important for spreading information about the topic under study. In this manner we are able to reveal the unresolved psychological issues that compel people to talk about the topic in the manner that they have done.

Case Study - Sorting the Coca-Cola Memes

The 5000+ memes gathered from Twitter were coded by an analyst to assign numerical values for each semantic filter. This produced a spreadsheet filled with numbers that represent the thematic resonance of each filter to every meme in the original database.


Case Study - Crunching the Numbers on Coca-ColaThe analysis revealed four high-level themes that explain public sentiment about the Coca-Cola brand. Each theme represents an unresolved tension about the feelings people harbor for this universally recognized piece of global culture.

Note how these findings suggest

Step 4 - Reveal the Psychological Drivers of CultureThe themes revealed in Step 3 are what we call meme dimensions. They are the resonance points in the culture that tell us why people are talking about the topic under study. They also tell us why people are inclined to share information, which means it is possible to get people to talk about these themes with others in their social network by speaking about them in the same way that they do.

We now perform another qualitative analysis on the meme dimensions to shed light on the psychological mechanisms at play. This is where the findings become richly nuanced and actionable.


Case Study - Psychology of the Emotion Dimension

In the Coca-Cola study, a prominent theme that stood out was the Love/Hate relationship people have with the brand. The general public is deeply ambivalent and conflicted, threatening the future of the company.

These feelings are quite strong, indicating that those who love the brand can easily become angered with thoughts of betrayal. Combined with the emphasis on dishonesty it becomes clear that the company’s negative social impacts place its most valuable asset—the intangible worth of its brand equity—in jeopardy.

Meme analysis reveals that the world’s most powerful brand could easily collapse if public sentiment sways toward dishonesty and hatred.

Step 5 - Create A Meme MapAt this point in the process we have so many insights to work with that we need to organize it in visual form. The tool we use to communicate strategic issues is called the meme map. The meme map is constructed by observing that memes do not act alone in the world. They have important relationships with each other that tell us how they help or hinder the spreading of different themes.


We organize all of the memes in the database into five categories based on how they orient around the high-level themes uncovered by the statistical analysis. These categories are inspired by the field of ecology and each tells us how one meme relates to all others in the cultural ecosystem. The five categories are:

✦ Defining Memes: What are the defining features of the topic? How is it thought about and understood? What are its essential emotional qualities and most central themes? These memes give answers through the diverse perspectives of key actors in the marketplace.

✦ Symbiotic Memes: What are the topics that spread easily on their own and also form natural synergies with the topic? These memes can boost its spreading power and increase adoption of key practices.

✦ Parasitic Memes: How does the conversation get pulled away from the topic’s core strengths? What are the distractions and diversions that take attention and resources away, thus limiting its capacity to spread? These memes are the parasites that sap the topic of energy and hinder adoption.

The DarwinSF Meme MapTM


✦ Hostile Memes: Who are the antagonists that want to see protagonists for the topic fail? How do they respond to the threat of the topic’s success? These memes actively fight against the spreading of the topic.

✦ Immune Deficiency Memes: What are the qualities of the topic that hinder its ability to spread? How is it handicapped by its internal makeup? These memes are the weak areas that need to be avoided or overcome in order to grow its marketplace more quickly and achieve larger gains.

By creating a map of the relationships between these five categories of memes, we are able to recommend tactics and strategies that help spread new ideas.

Step 6 - Prepare the DeliverablesWe are now ready to prepare deliverables for the client. These may take the form of strategy briefs, slide decks, infographics and instructional materials. We guide our client through the most important findings and help them incorporate this new information into their operations.

Case Study - A New Brand Strategy for Coca-Cola

Increasing concern about social impacts is placing this global brand in jeopardy. Acknowledging the immense value of the Coca-Cola brand, we recommend that the company thoughtfully begin to address past harms to restore trust with the public.

Also, this analysis reveals an opportunity to leverage the love people have for Coke to transition its core business strategies toward a configuration of genuine corporate responsibility while benefitting from this leadership. Along the way care must be taken not to activate hostile memes that could damage their brand further.


As the Coca-Cola case study demonstrates, meme research brings alive the richness of deep cultural contexts around specific topics. Any organization seeking to alter social norms, introduce new ideas, or make sense of the changing marketplace will benefit greatly from the power of this advanced approach to cultural research.

An Evolutionary Approach to Cultural ResearchHopefully by now it is clear how powerful an approach this is, combining the dual strengths of qualitative and quantitative methods to achieve mathematical rigor without loss of interpretative depth and breadth. An additional layer of sophistication comes in when the entire process is repeated at a later time. Armed with the meme insights that arise from each round of study, our clients go out and interact with their constituents.

Every time they do so, the world is changed in some way. Unfortunately most cultural research methods lack any ability to measure impact. We overcome this by taking an evolutionary approach where the insights gained in one study are then applied iteratively as design criteria for encouraging cultural change. With multiple iterations, the cultural ecosystem is able to evolve (just like in biology where the introduction of new species will alter how an ecosystem changes in time).

Along the way, our clients are able to engage their constituents where they are and help them get to where they need to go. This is cultural design in action!


A Note About Us

At Culture2 Inc. our mission is to help good memes spread. We are living in a world where “good memes are not good memes” — the most influential ideas are often destructive and harmful. They have had more success at spreading than the ideas that humanity needs to survive and flourish into the foreseeable future. As a social impact company, we recognize that doing good is a great way to earn a living. Our advanced meme technologies are only used in the service of this worthy ideal. We live our values and hold the integrity of our mission as a core operating principle.


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Culture Design 101