Mari-Klara Stein's presentation from the workshop Language Technology and Business, held at Copenhagen Business School on 9 June 2015 with the support of the CBS Competitiveness Platform. http://bit.ly/CBSCompeteLangTechBusiness Mari-Klara Stein Assistant Professor IT Management Department CBS mst.itm@cbs.dk

1. Emotions and Facebook Data
Language Technology and Business Workshop. June 10th, 2015.
Emotions and Facebook Data
Mari-Klara Stein
Assistant Professor
IT Management Department
CBS
mst.itm@cbs.dk

2. Emotions and Facebook Data
Language Technology and Business Workshop. June 10th, 2015.
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Context: Social Media & Emotions
• ICTs are implicated in most emotion-related processes (Stein et al. 2015; Zhang
2013; Beaudry and Pinsonneault 2010)
• Social media in particular can facilitate and influence the generation of feelings,
for example, through emotional contagion (Kramer et al. 2014) and the direct
expression of feelings through tagging:
• Facebook added the feature of sharing one’s feeling or mood with status updates in
2013
• Twitter and Instagram allow for the use of hashtags that often either directly label a
post with an emotion or convey a more complex ‘emotional script’* (e.g., #YOLO;
#jesuischarlie)
• Social media provide ripe environments for new emotional scripts to develop and
traditional ones to evolve (e.g., ‘meh’, ‘awesome’, ‘blessed’ on Facebook)
* Emotional scripts refer to sets of behavioral responses used to express emotions in particular circumstances (what
is appropriate, relevant, expected). People have a great number of scripts, these develop over a lifetime of
experience and social learning.

3. Emotions and Facebook Data
Language Technology and Business Workshop. June 10th, 2015.
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So What? Business Perspective
• The level of diffusion of social media (especially Facebook) has lead to a situation
where most businesses consider it a ‘must’ to be present on social media
• How to take advantage of the troves of data generated by users on social media
is one of the biggest current challenges (Culnan et al. 2010; Mandviwalla and
Watson 2014; Vatrapu 2013)
• Social media analytics involves the development and evaluation of “informatics
tools and frameworks to collect, monitor, analyze, summarize, and visualize social
media data” (Abrahams et al. 2013: 872):
• Sentiment, affect, semantic, network, etc. analyses….

4. Emotions and Facebook Data
Language Technology and Business Workshop. June 10th, 2015.
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Where do Language Technologies
Come In?
• The focus of this workshop: What is the role of language technology in
helping businesses understand and take advantage of, for example,
social media?
• My focus: Importance of understanding the basics of the phenomenon
under study and its potential implications for business before ‘playing
around with the data’

5. Emotions and Facebook Data
Language Technology and Business Workshop. June 10th, 2015.
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Basics of the Phenomenon: Emotions
Before ‘playing around with data’, we need to understand the phenomena we are
dealing with
• What is a ‘Facebook feeling’?
• How can we measure it?

6. Emotions and Facebook Data
Language Technology and Business Workshop. June 10th, 2015.
Definitions: What is a ‘Facebook feeling’?
• Emotions are a very demanding research object (Kopelman et al. 2006):
• different theoretical traditions; many concepts (feelings, moods, affect, temperament,
etc.); limited consensus on definitions (Barsade and Gibson 2007; Scherer 2005).
• difficult to collect (expressed vs. experienced emotions?)
• One common definition: emotion is an “episode of interrelated, synchronized
changes in the states of all or most of the five organismic subsystems
(cognitive, neurophysiological, motivational, motor expression and subjective
feeling) in response to the evaluation of an external or internal stimulus event
as relevant to major concerns of the organism” (Scherer 2005: 697).
• Feeling, thus, captures only one component of emotions - the subjective
experience of it.
• possibility that subjective experience and outward expression are incongruent…
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7. Emotions and Facebook Data
Language Technology and Business Workshop. June 10th, 2015.
How to describe and measure a
‘Facebook feeling’?
A dimensional approach
(Scherer, 2005):
• Valence, arousal,
intensity, duration,
etc.
• Valence and arousal
most common and
most widely agreed
upon
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8. Emotions and Facebook Data
Language Technology and Business Workshop. June 10th, 2015.
How to describe and measure a
‘Facebook feeling’?
A typological approach
(Ashkanasy, 2003; Fischer, et al.,
1990):
• Basic emotions (universal
emotions to the human
species, developed through
evolution)
• Sub-ordinate emotions
(socially learned complex
‘scripts’ that build on basic
emotions)
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9. Emotions and Facebook Data
Language Technology and Business Workshop. June 10th, 2015.
How to describe and measure a
‘Facebook feeling’?
A process approach
(Elfenbein, 2007):
Emotions unfold
chronologically through a
rule-governed sequence
of automatic
components. The
controlled components
arise at specific stages
but are optional and can
end at any point. These
steps unfold so quickly
that they can appear
together to represent a
single phenomenon.
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10. Emotions and Facebook Data
Language Technology and Business Workshop. June 10th, 2015.
Some Known Business Implications
1. Feelings (emotions) are contagious:
• When positive expressions were reduced, people produced fewer positive
posts and more negative posts; when negative expressions were reduced,
the opposite pattern occurred. [...] Emotions expressed by others on
Facebook influence our own emotions, constituting experimental evidence
for massive-scale contagion.” (Kramer, et al., 2014).
2. Feelings (emotions) influence behavior (e.g., sharing, posting, commenting)
3. Arousal matters as much (if not more) than valence:
• High arousal content (positive and negative) is most highly shared (Berger
and Milkman, 2012; DeChoudhury, et al., 2012; Stieglitz and Dang-Xuan,
2013)
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11. Emotions and Facebook Data
Language Technology and Business Workshop. June 10th, 2015.
And So Much We Don’t Know…
• Which basic emotions / ‘emotional scripts’ are most commonly expressed
online?
• Which basic emotions / ‘emotional scripts’ are most contagious online?
• How are ‘emotional scripts’ evolving online? How are new ones created?
• Do different emotions influence different online behavior (sharing, posting,
commenting, etc.) differently?
• What are the stimuli that elicit emotions in online environments?
• How do people reappraise and regulate their emotions online?
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12. Emotions and Facebook Data
Language Technology and Business Workshop. June 10th, 2015.
Now We Can ‘Play with the Data’ J
Dan, Chris and Rasmus ...
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13. Emotions and Facebook Data
Language Technology and Business Workshop. June 10th, 2015.
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Thank you for your attention! "
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Questions, Comments?"

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Language Technology and Business Workshop. June 10th, 2015.
References
• Abrahams, A. S., Jiao, J., Fan, W., Wang, G. A., and Zhang, Z. 2013. ‘What's buzzing in the blizzard of buzz? Automotive component isolation in social media
postings,’ Decision Support Systems (55:4), pp. 871-882.
• Ashkanasy, N. M. 2003. ‘Emotions in organizations: A multilevel perspective,’ Research in multi-level issues, 2, pp. 9-54.
• Barsade, S. G., and Gibson, D. E. 2007. ‘Why does affect matter in organizations?’ The Academy of Management Perspectives (21:1), pp. 36-59.
• Beaudry, B.A., and Pinsonneault, A. 2010. ‘The Other Side of Acceptance: Studying the Direct and Indirect Effects of Emotions on Information Technology Use,’ MIS
Quarterly (34:4), pp. 689-710.
• Berger, J., & Milkman, K. L. (2012). What makes online content viral? Journal of marketing research, 49(2), 192-205.
• Culnan, M. J., McHugh, P. J., and Zubillaga, J. I. 2010. ‘How large US companies can use Twitter and other social media to gain business value,’ MIS Quarterly
Executive (9:4), pp. 243-259.
• De Choudhury, M., Counts, S., & Gamon, M. Not All Moods are Created Equal! Exploring Human Emotional States in Social Media.
http://research.microsoft.com/apps/pubs/default.aspx?id=167866
• Elfenbein, H. A. (2007). Emotion in Organizations: A Review and Theoretical Integration. The academy of management annals, 1(1), 315-386.
• Fischer, K. W., Shaver, P. R., & Carnochan, P. (1990). How emotions develop and how they organize development. Cognition and Emotion, 4, 81–127.
• Kopelman, S., Rosette, A.S., and Thompson, L. 2006. ‘The three faces of Eve: Strategic displays of positive, negative, and neutral emotions in negotiations,’
Organizational Behavior and Human Decision Processes, 99, pp. 81-101.
• Kramer, A. D., Guillory, J. E., and Hancock, J. T. 2014. ‘Experimental evidence of massive-scale emotional contagion through social networks,’ Proceedings of the
National Academy of Sciences (111:24), pp. 8788- 8790.
• Mandviwalla, M., and Watson, R. 2014. ‘Generating Capital from Social Media,’ MIS Quarterly Executive (13:2), pp. 97-113.
• Scherer, K. R. 2005. ‘What are emotions? And how can they be measured?’ Social science information (44:4), pp. 695-729.
• Stein, M. K., Newell, S., Wagner, E.L., and Galliers, R. 2015. ‘Coping with Information Technology: Mixed Emotions, Vacillation, and Nonconforming Use Patterns,’ MIS
Quarterly (39:2), pp. 367-392.
• Stieglitz, S., and Dang-Xuan, L. 2013. “Emotions and information diffusion in social media—Sentiment of microblogs and sharing behavior,” Journal of Management
Information Systems (29:4), pp. 217-248.
• Vatrapu, R., 2013. Emerging Dimensions of Technology Management. In Understanding social business. ed. K.B. Akhilesh. Springer Science+Business Media. New
Delhi, pp. 147-158.
• Zhang, P. 2013. ‘The affective response model: a theoretical framework of affective concepts and their relationships in the ICT context,’ MIS Quarterly (37:1), pp.
247-274.
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