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Game or measurement? Algorithmic transparency and the Klout score

Game or measurement?
Algorithmic transparency and the Klout score
Devin Gaffney
Oxford Internet Institute
University of Oxford
1 St. Giles
Oxford, OX1 3JS
United Kingdom
Cornelius Puschmann
Berlin School of Library and Information Science
Humboldt-Universität zu Berlin
Unter den Linden 6
10099 Berlin
Klout 1is an Internet service that claims to measure an
individuals influence by aggregating information from a va-
riety of social media platforms. We briefly examine Klouts
approach to measuring influence and argue that the Klout
scores lack of algorithmic transparency undermines its sta-
tus as a trustworthy metric. We further argue that Klout
and similar services “gamify” the notion of influence in ways
that encourage competitive behavior among users in ways
which are detrimental to the quality of measurement in a
scientific sense, instead encouraging a gamified notion of in-
fluence. We conclude that only an approach to measure-
ment that is based on transparency has a real chance of
gaining trust, and that only a widely trusted metric may
serve as a reliable indicator of influence. Beyond the case
of Klout, context, theoretical soundness, algorithmic trans-
parency, and user agency are general issues that must be
dealt with for any entity attempting to measure influence in
online social networks.
Klout, Social Media, Influence Measurement
A flurry of news articles have recently explicated the im-
portance of Klout scores as a point of judgment in cases
ranging from access to VIP areas of a club to job offers from
potential employers [2, 7, 11]. This to be expected – what is
the utility of a service that purports to definitively measure
influence unless these scores are employed beyond Klouts
domain as a proxy for social media authority? While this is
perhaps not surprising, it is problematic, and Klout exem-
plifies many of the issues that arise when relying on metrics
provided by a commercial third party, and belies a grow-
ing dependence on such metrics both within and outside of
academia [5].
Individuals, communities, and publics interacting online do
not form a homogenous whole. It is essential for researchers
to keep in mind that context matters, and that what ap-
plies to one set of people may not apply to another. As an
example, [8] noted distinct audience practices surrounding
different influential Twitter accounts in Tunisia and Egypt
in 2011. Even the most exhaustive works surrounding so-
cial media influence research stops short of claiming causal-
ity or predictive power, despite the strong indications they
find [5, 1]. Influence is a profoundly contextually-bounded
notion – what defines it in one community may differ dras-
tically from another communitys definition. Klouts ap-
proach to influence assumes an ability to reduce the contex-
tual complexity provided by seemingly unambiguous signals
(retweets, likes, follower/friend-relations among users) into
a one-dimensional, 0-100 index score [3]. While this total-
ization is of obvious importance when seeking to establish a
commercial standard, it simplifies the meaning of these signs
and inevitably raises questions of agency and legitimacy.
Successful operationalization of influence is a precondition to
proposing a scientifically sound measurement – what makes
someone influential to whom has to be systematically de-
scribed before it can be quantified. Another condition is
that what is being measured should not be influenced by
the process of measurement, i.e. it should be observed un-
der natural conditions. Finally, subjectivity must be ad-
dressed: Who is measuring? Who is being measured? What
is the purpose of the measurement and what potential for
misuse exists? While counting the number of cookies in a
jar can be regarded as value-neutral in the sense of being
reproducible, reliable and not bound to a single context of
analysis or intention, measuring influence immediately raises
questions of how the particular judgment was reached. The
Klout score renders the context of analysis irrelevant and
encourages systematic comparisons of scores among users –
a defining, game-like feature of the platform. The score and
the subjective quality of influence thus lose sight of one an-
other and the score becomes an entity of its own, more akin
to a currency than to a metric.
A major component to the legitimacy of analytical methods
is the degree to which they are accessible for scrutiny and
reproduction. In the case of Google, the analytic methods it
developed were laid out in general terms in conjunction with
its operationalization [9, 4]. While PageRank has certainly
changed drastically in the intervening decade owing to the
various business directions the service has gone in, it seems
that the initial transparency of the algorithm paved the way
for users to establish a relationship of trust to the search en-
gine. For obvious competitive reasons, not all startups are
in a position to publish white papers documenting their al-
gorithms to the general public. But disclosing the details of
their system would be especially relevant for a service that
measures something as subjective and mutable as influence,
a parameter that relies on widespread acceptance to be con-
sidered authoritative. Furthermore, transparency is not a
switch – it is a gradient. Though Klout may be at risk by
disclosing a trade secret in the short run, moving towards
a more transparent model in the long term would under-
pin Klouts status as a reliable metric. In the contemporary
model, without generalized knowledge about the system, it
is impossible to trust Klout, leaving room for speculation
about the soundness of their approach, and academics rely-
ing on it are on very shaky grounds [10].
Because the kind of measurement delivered by Klout is so
obviously not value-neutral, it is crucial to provide users
with a meaningful form of agency beyond seeking to raise
their score to ever-higher levels. While many users cer-
tainly wouldnt use all the bells and whistles available to
modify what defines influence in their niche, those who do
will be given a much better metric. Necessarily, this elimi-
nates the universal relative comparison of scores, which does
nothing to improve analytical knowledge and everything to
encourage competition. In many ways, Klout has already
jumped the analytical shark by shifting their service away
from the core metrics available for several years and to-
wards a much more gamified experience via achievements
(awards for various activities on the site) and perks (cross-
promotional events with partner goods and services) [6]. In
doing this, Klout effectively de-emphasizes the importance
of its analytics service, and cheapens the value such a system
could have for its users.
[1] E. Bakshy, J. M. Hofman, W. A. Mason, and D. J.
Watts. Everyones an Influencer: Quantifying
Influence on Twitter. Hong Kong, China, February
9-12 2011. WSDM11.
[2] A. Blow. Can your Klout score land you a job?
your-klout-score-land-you-a-job, April 25
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Retweet: Conversational Aspects of Retweeting on
Twitter. In System Sciences (HICSS), 2010 43rd
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[5] M. Cha, H. Haddadi, F. Benevenuto, and K. P.
Gummadi. Measuring User Influence in Twitter: The
Million Follower Fallacy. pages 10–17, Washington,
DC, May 23-26 2010. Proceedings of the Fourth
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[6] S. Deterding, D. Dixon, R. Khaled, and L. Nacke.
From Game Design Elements to Gamefulness:
Defining ”Gamification”. Tampere, Finland,
September 28-30 2011. MindTrekˆa ˘
[7] B. Landman. Are You a V.I.P.? Check Your Klout
scores-sort-out-social-media-stars.html, November 18
[8] G. Lotan, E. Graeff, M. Ananny, D. Gaffney, I. Pearce,
and danah boyd. The Revolutions Were Tweeted:
Information Flows during the 2011 Tunisian and
Egyptian Revolutions. International Journal of
Communications, 5:1375–1405, 2011.
[9] L. Page, S. Brin, R. Motwani, and T. Winograd. The
PageRank Citation Ranking: Bringing Order to the
Web. Technical Report 1999-66, November 1999.
[10] D. Quercia, J. Ellis, L. Capra, and J. Crowcroft. In
the Mood for Being Influential on Twitter. Boston,
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[11] S. Stevenson. What Your Klout Score Really Means. klout/all/1,
April 24 2012.
... However, they have received several critics and have been the focus of several controversies regarding how the measurements are computed or the effect that spam-bots might have on the algorithms. As most of the commercial measures do not publicly state how scores are computed, they are not accessible for scrutiny or reproduction, which might compromise their trustworthiness [Gaffney and Puschmann, 2012]. ...
... Considering that there is no consensus on what means to be an influential user [del Campo-Ávila et al., 2013;Gaffney and Puschmann, 2012], this work aims at analysing the human perception of influence. The presented metric was compared not only to several commercial metrics, but also to a human assessment of user influence. ...
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People's influence has been the subject of study of several social and humanities disciplines. Lately, the study of user's influence in micro-blogging platforms arises as an important issue. Although social influence or prestige can be defined as the potential or ability of an individual to engage others in a certain act, or to induce others to behave in a particular manner, there is no global consensus on what means to be an influential user. This work aims at shedding some light on how to assess user influence by proposing a novel metric of user influence based on analysing user behaviour regarding both content-based and topological factors. The metric does not only consider each user individually, but also aims at assessing the interactions with his/her neighbourhood. The statistical analysis performed confirmed that only analysing the topological factors is not sufficient for accurately assessing the influence of users. Instead the published content and its influence over the neighbourhood of users has to be also analysed. A comparison with a human assessment of user influence showed that the factors considered by the proposed metric are truly relevant for assessing people's influence.
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Son yıllarda işletmeler rekabet avantajı yaratmada kritik rol oynayan yetenekli çalışanları işe almak için çeşitli yöntemler kullanmaktadır. Bunlar içerisinde en önemlisi, sosyal medyanın etkin kullanımıdır. Başta Amerika Birleşik Devletleri olmak üzere işe alımlarda adayların sosyal medya puanı referans kabul edilmekte ve bu puanı değerlendirebilmek için adayların klout puanı incelenmektedir. Klout puanı, bir kişinin sosyal medya sitelerindeki popülerliğini ve etkisini göstermektedir. Sosyal medyanın işe alımlardaki etkinliğinin artmasıyla birlikte, klout puanının da ülkemizde yakın bir zamanda işe alımlarda etkili olacağı değerlendirilmektedir. Bu çalışmada, klout puanı hakkında bilgi verilmiş ve klout puanının işe alımlarda etkili olup olamayacağı sorgulanmıştır. In recent years, businesses use a variety of methods to recruit talented employees which play a critical role in creating competitive advantage. The effective use of social media is one of the most important of these methods. Particularly in the United States, applicants' social media scores are accepted as reference in recruitment and applicants' klout scores are analyzed in order to assess this score. Klout score shows a person's popularity and effectiveness at the social media sites. With the increasing effectiveness of social media in recruitment, klout score is considered to be effective in recruitment in our country in the near future. In this study, information was given about klout score and whether it will be effective or not in recruitment was questioned.
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Are You a V.I.P.? Check Your Klout Scoreklout- scores-sort-out-social-media-stars.html
  • B Landman
B. Landman. Are You a V.I.P.? Check Your Klout Score. scores-sort-out-social-media-stars.html, November 18 2011.
Can your Klout score land you a job?
  • A Blow
A. Blow. Can your Klout score land you a job?, April 25 2012.
What Your Klout Score Really Means
  • S Stevenson
S. Stevenson. What Your Klout Score Really Means. klout/all/1, April 24 2012.