Presentation on theme: "Web 2.0 4.1.09 Beyond Buzz: On measuring a conversation Kate Niederhoffer, Ph.D Marc A. Smith, Ph.D Dachis Corporation Telligent Systems."— Presentation transcript:
1WebBeyond Buzz: On measuring a conversation Kate Niederhoffer, Ph.D Marc A. Smith, Ph.D Dachis Corporation Telligent Systems
2Why us?Kate NiederhofferPh.D UT Social PsychologyBuzzMetrics/Nielsen Online, Measurement ScienceDachis Corporation - Methodology, Social Business DesignMarc SmithPh.D UCLA SociologyMicrosoft Research, Community Technologies GroupTelligent Systems – “Harvest” reporting and analysis tools for social media platforms and systemsNote: This is a conceptual address. We’re talking about ideas; each of our companies have distinct methodologies in place related to these concepts.
3Why are we here?Demonstrating the depth of buzz; ways to think about signal within vast universe.Going beyond buzz; learning more about individuals.
4Why are we here?Highlighting the unique roles individuals play in communities that afford the conversation.Illustrating that aggregated relationships are network structures.
6Blogs were all the rage In 2005, clients attracted by novelty: Simple question: What’s my buzz?- How much?- Good or bad?Incremental improvement: How “important” is it?- Are “Influencers” talking?- How many eyeballs exposed?- Engagement?However, all superficially measured;limited scope of what’s important: what kind of influence?
7Blogs are now featuresToday’s “media” enable richer social interaction-- and, leave a path of data with more opportunities to capture depthBuzz levels, page views, followers, in isolation miss big pictureMust take advantage context to tell whole story and capture value
8Social networks are all the rage, but rarely do we think about social metrics We need to stop blackboxing:"When a machine runs efficiently, when a matter of fact is settled, one need focus only on its inputs and outputs and not on its internal complexity. Thus, paradoxically, the more science and technology succeed, the more opaque and obscure they become."- Bruno LatourEven if a conversation is running smoothly, we must figure out what makes it tick.
9(Hampton &Wellman, 1999; Paolillo, 2001; Wellman, 2001) Social NetworkTheoryCentral tenet:Social structure emerges fromthe aggregate of relationships (ties)among members of a populationPhenomena of interest:Emergence of cliques and clustersfrom patterns of relationshipsCentrality (core), periphery (isolates),betweennessMethods:Surveys, interviews, observations, log file analysis, computational analysis of matricesSource: Richards, W. (1986). The NEGOPY network analysis program. Burnaby, BC: Department of Communication, Simon Fraser University. pp.7-16(Hampton &Wellman, 1999; Paolillo, 2001; Wellman, 2001)
10Context of a conversation RelevanceSignalWhere’s the signal in the noise?MindsetPersonWhat else do we know about the individuals?RolePersonaWhat is the pattern of connections?EcosystemEnvironmentWhat is the dynamic, en masse?
11We didn’t used to have a holistic overview of the Earth; we don’t have one of social media. It’s hard to find signals in all the noise; sometimes you aren’t even picking up on all the noise
12Context of a conversation RelevanceWhere’s the signal in the noise?MindsetRoleEcosystem
13We don’t always know what we want to know! Relevance todayAs a user, easy to relate to issues with pre-determined filters.As an enterprise, complexity increases.We don’t always know what we want to know!
14Relevance: Which filters are in place to strengthen the signal? Identifying your filters can be inductive:What are people really saying?Which concepts differentiate the posts that mention you vs. posts that don't?* Source: Nielsen Online, 2008All terms on your map have a correlation to the central concept; the closer a word appears to the center, the stronger the association.The groupings of terms indicate the dimensions of discussion: micro-conversations within a broader discussion.
15Relevance is multi-faceted Rather than looking at associations with, as compared to without, consider discussion this week as compared to discussion over the past year.Not what’s being said about her in a more recent timeframe, but instead when you control for what’s said about her in general, what pops?* Source: Nielsen Online, 2008
16Relevance - SummaryInformation can be visualized in so many different ways; don’t take it for granted.Listening can be limited if you’re exclusively looking for something in particular; broaden your net. Be inductive. Let the data speak for itself.
17Globally coherent activity is a beautiful thing, but really can’t appreciate it in full– or experience it without tapping into the individual constituents producing the signal.
18Context of a conversation RelevanceMindsetWhat else can we know about the individuals?RoleEcosystem
20Mindset What else can we know about the person in conversation? By measuring the types of words used, we can tap into how people ‘slice’ their worlds.Linguistic style is closely tied to:Demographics (e.g. age, sex, class)Emotion (e.g. depression, deception)Cognitive style (e.g. complex thinking)Personality (e.g. Neuroticism)FindingsLinguistic CuesAre you self-oriented?Pronoun use: I and WeAre you living in ‘the now’?Past, Present, Future tenseWhat is your emotional tone?Positive vs. NegativeAre you abstract or concrete?Articles: “a” vs. “the”Nouns vs. verbse.g. Pennebaker, Mehl, Niederhoffer, 2003
21When people make recommendations on blogs, is there something deeper going on? “Got the next three PW/GS games for my birthday. And I am one happy gal, there was some stuff that I absolutely LOVED and I would definitely recommend the game to anyone who owns a PS3 regardless of its flaws -- which really were at their heart personal quibbles of mine so your mileage may vary. Plus, I cried like a b*$$ at the end. That's got to be saying something.”
22Getting into the Engaged Mind Recommendations have:More pronouns: intimacy with both the brand/product/ service being recommended, and those to whom they’re recommending.More verbs: sharing experience more than discussion of concrete features.* all differences significant at p<.01 level
23“Invisible” language gives us clues about individuals, and groups
24Changes in work atmosphere, captured in words Engineers, economists programmers collaborating on economic simulations of disastersComplexity of thought (-)Cohesion (-)Work information (-)Negative emotion (+)Funding lostTausczik, Scholand, and Pennebaker, 2009
25“Connected Age”: relationships are groundwork of work Social: niceties (lol), affirmations (cool), coordination (call), broad communication (http, thinking)Work: economic (production, supply), analytic (results, problem)
26Mindset- SummaryLanguage is a good way to go beyond the surface and better understand constituents without self- report biases (or effort).Metrics in the hands of users (yourselves) are helpful: know thyself, know how you’re perceived.
27Beyond thoughts and feelings, who comes to roost?
28Context of a conversation RelevanceMindsetRoleWhat is the pattern of connections?Ecosystem
29Social Network Analysis with NodeXL: Identify different roles in social media spaces
31Distinguishing attributes: Answer personOutward ties to local isolatesRelative absence of trianglesFew intense tiesReply MagnetTies from local isolates often inward onlySparse, few triangles
32Distinguishing attributes: Answer personOutward ties to local isolatesRelative absence of trianglesFew intense tiesDiscussion personTies from local isolates often inward onlyDense, many trianglesNumerous intense ties
33Answer Person Signatures See Picturing Usenet in JCMCDiscussionPeople
35Role – SummaryNetwork awareness, like court vision enables strategic play. Know which positions/players are on your team.Social media behavior is differentiated. Rare (~.5-2%) roles are critical and must be cultivated.E.g. Clear and consistent signatures of an “Answer PersonLight touch to numerous threads initiated by someone elseMost ties are outward to local isolatesMany more ties to small fish than big fish
43Mapping Newsgroup Social Ties Microsoft.public.windowsxp.server.general43Two “answer people” with an emerging 3rd.
44Research shows social media spaces vary and roles are present Adamic et al. WWW 2008
45Ecosystem- Summary Social media is about collective action. A balance of roles and strategies is critical for a healthy/ successful collective good.Harvesting the common good takes many forms, and is the ultimate goal of social media.
46Why does this matter?This is not measurement for the sake of measurement; we need to measure conversations in order to manage social business.Measuring conversations is about measuring the context in which those conversations arise.Value is an intermediate step in calculating ROI. Moot to bypass it.Techniques from social science help capture “the immeasurable” in social media and the enterprise.The future of conversations- the enterprise being one- - is about cultivating ecologies of the right balance of relationships.
47Thank You email@example.com firstname.lastname@example.org Questions?
50How uniform are social media producing groups? Small GroupsIndividualsUniform Large GroupsHeterogeneousVariable Contribution Large GroupsVariable Contribution Large GroupsHow uniform are social media producing groups?
51Social Science Theory and Method Interactionist SociologyCollective Action DilemmasCentral tenet Focus on the active effort of accomplishing interaction Phenomena of interest Presentation of self Claims to membership Juggling multiple (conflicting) roles Frontstage/Backstage Strategic interaction Managing one’s own and others’ “face” Methods Ethnography and participant observation (Goffman, 1959; Hall, 1990)Central tenetIndividual rationality leads to collective disasterPhenomena of interestProvision and/or sustainable consumption of collective resourcesPublic Goods, Common Property, "Free Rider” Problems, TragediesMethodsSurveys, interviews, participant observation, log file analysis, computer modeling(Axelrod, 1984; Hess, 1995; Kollock & Smith, 1996)