information behaviour and emotions · 2017-09-07 · school of information studies why study...

School of Information Studies

Information Behaviour and Emotions

Hamid R. JamaliSIS Research Seminar Series

6 September 2017


Contents

• Some background

• Terminology

• Emotions in LIS

• Methods of studying emotions

• A study on filtering and emotion


Background

Emotion is studied by various disciplines: sociology, cognitive science, psychology, nursing, education, neuroscience, communication, computer science, … and of course information science

• Erik Erikson, 1950, theory of socio-emotional development

• Bloom et at., 1956, taxonomy of affective domain

• Herbert Simon, 1967, identified emotion as a major challenge in cog. Sci, due to its effect


Some applications

• Affective computing (Picard, 1997)

• Emotional design (Norman, 2004)

• Context-aware information systems

• Affective information retrieval

Emotional design is incorporating emotions in the design of effective and pleasurable systems that are natural for humans to understand and use’ (Picard, 2004).

Affective computing is “computing that relates to, arises from, or deliberately influences emotions…. it includes giving a computer the ability to recognize and express emotions, developing its ability to respond intelligently to human emotions, and enabling it to regulate and utilize its emotions.” (Picard, 1997, p. 3)

Affective information retrieval (IR) system is an IR system design that is attuned to searchers’ emotional needs (Lopatovska, 2009)


Terminology

Feeling Affect Mood Emotion

Emotion: No agreement on definition, 90+

definitions

No agreement about its relationships with

mood, affect, feeling and other terms.

(Kleinginna & Kleinginna, 1981)


Differentiation: Core Affect

Definition: neurophysiological state

consciously accessible as a simple primitive

non-reflective feeling most evident in mood

and emotion but always available to consciousness

Examples: pleasure, displeasure, tension, relaxation

(Ekkekakis, 2012)


Differentiation: Emotion

Definition: a complex set of interrelated sub-events concerned with a specific object core affect, (b) overt behaviour congruent with the emotion (e.g., a smile or a facial expression of fear), (c) attention directed toward the eliciting stimulus, (d) cognitive appraisal of the meaning and possible implications of the stimulus, (e) attribution of the genesis of the episode to the stimulus, (f) the experience of the particular emotion, and (g) neural (peripheral and central) and endocrine changes consistent with the particular emotion. Because emotional episodes are elicited by something, are reactions to something, and are generally about something, the cognitive appraisal involved in the transaction between person and object is considered a defining element.

Examples: fear, anger, jealousy, pride, love(Ekkekakis, 2012)


Differentiation: Mood

Definition: the appropriate designation for

affective states that are about nothing

specific or about everything-about the

world in general. Mood lasts longer than

emotion, and is diffuse and global as

opposed to specific.

Examples: anxious, depressive(Ekkekakis, 2012)


In other words

• Affect is a generic term that covers a broad range of feelings that people experience. It’s an umbrella concept that encompasses both emotions and moods.

• Emotions are intense feelings that are directed at someone or something.

• Moods are feelings that tend to be less intense than emotions and that often (though not always) lack a contextual stimulus.

(Robbins & Judge, 2012, p. 260)


Image from Robbins & Judge (2012, p. 261)


Relationship of emotion and mood

They influence one another

• Strong and deep emotion can result in a

change of mood

• Getting a great job

• Mood can reinforce an emotion

• Overreacting to someone while in a bad

mood


Emotion in LIS has been conceptualized as

• being caused by or arising out of situations, tasks, or contexts or their subparts

• being attributes of persons – their personalities, demography, genetics, physiology, or past experiences

• being causes of inhibiting or activating motivations

• causing or leading to specific actor goals or activities

• being encoding traces left in information, message, or text packages

• serving as states of being that have informational value (Dervin & Reinhard, 2007, p. 55)


Why study emotions in LIS

“Emotions, we now know, change the way the human mind solves problems—the emotional system changes how the cognitive system operates." (Norman, 2004). Affective variables drive cognitive information behaviour through a person’s interests, motivation, feelings, and persistence. Recent research suggests that uncertainty contributes to cognitive load and negatively affects success, while optimism positively affects it. Therefore, a focus on the interaction of affect and cognition, particularly studies examining the varieties of affect that arise in different situations and their impact on cognition, is necessary to understanding the information behaviour of various groups.”

(Nahl et al., 2005)


Why study…

Information reception is a behaviour that involves all three biological systems: sensorimotor, cognitive and affective (Nahl, 2007)

Positive affect facilitates cognitive processing, while negative affect inhibits and disturbs it (Lopatovska, 2009)

Information search is an affective experience characterized by positive and negative feelings that impact attention, memory, performance, and judgments (Brave, Hutchinson & Nass, 2005)

Affect can cause selective attention or selective memory in a wide variety of circumstances, leading to compelled non-use of information (CNI). Many of these circumstances appear to involve CNI as a response to threat: threat to life, threat to health, or threat to a person's ego (Houston, 2009)


Why study…

Image from https://en.wikipedia.org/wiki/Emotion


Background in LIS

• Information Search Process

(Kuhlthau, 1991)

• Library anxiety (Onwuegbuzie, Jiao & Bostick, 2004)

• Research by other researchers

such as D. Nahl, Belkin, Wilson


Kuhlthau’s Information search process

Uncertainty @ initiation stage

Confusion, doubt or frustration @ exploration stage

Sense of direction @ collection stage

Image from: http://wp.comminfo.rutgers.edu/ckuhlthau/information-search-process/


Context in HIB

Constituent parts of context

• Task. Any goals, tasks, actions or activities associated with what the user is doing.

• Spatiotemporal. Attributes relating to the current time, location, direction, and so on.

• Personal. The user’s physiological context, mental state, preferences, and so on [includes emotions].

• Social. The user’s role, status, and relationships with other individuals.

• Environmental. Factors including temperature, light, humidity, and, on a slightly different note, the information resources accessed by the user.

(Myrhaug and Goker, 2003)


Some findings from past studies

While positive feelings were more common and were associated more often with thoughts about results, negative feelings were associated more often with thoughts related to the system, search strategy, and task (Tenopir et al., 2008).

Higher happiness levels before and during the search correlates with better feelings after the search, but also correlates with worse search outcomes and lower satisfaction, suggesting that, perhaps, it pays off to feel some “pain” during the search to “gain” quality outcomes (Gwizdka and Lopatovska (2009).


Some findings from past studies 2

More frequent happiness expressions coincides with longer time spent on tasks, more time spent reviewing results as well as entering more unique queries. The more thorough the searcher, the more rewarding results the searcher gets and the happier s/he feels. The sadder and less happy one feels, the sooner s/he will end the search because there is no positive reinforcement to continue (Lopatovska’s (2009).


Some findings from past studies 3

Being exposed to a political campaign triggers several emotions but only anxiety boosts information seeking and learning. While anger, enthusiasm, and anxiety could lead people to claim they would pay attention to the campaign, anger actually depresses total information seeking (Valentino et al., 2008).

Sharing happy information: individuals considered sharing happy information important to their friendships and relationships (Tinto & Ruthven, 2016)


Measuring emotions/ affects - 1

Self report & usually retrospective measures

• Mostly used in psychology and LIS

• Includes think aloud protocols,

questionnaires, pre- & post- session

interviews, & diaries

(Lopatovska, 2009)



Measurement of real-time neuro-physiological measures associated with emotions such as brain activity images, pulse rate, blood pressure, skin conductance, respiration data (using sensors and devices)

• Usually used in HCI

• Can limit participants’ mobility and cause distraction of emotional reactions

• May not distinguish between specific emotions (e.g. anger or fear)

• Needs expertise and equipment



Observer method i.e. a third-person observes, recognises and codes emotions manifested in participants’ facial expressions, vocal changes, verbal content and bodily movements.

• Used in HCI and psychology

• Observer needs to be an expert trained in Specific Affect Coding System (SPAFF) or Facial Action Coding System (FACS) (Larsen & Fredrickson, 1999)

• It is an unobtrusive method of data collection

• Is limited to analysis of present expressions of emotional states (cannot be used for meaning of emotions, emotional memories or predictions)



Automatic facial expression analysis

systems (AI)

• Quick, unobtrusive, and relatively accurate

• Systems could also classify vocal and

bodily changes

• Does not take into account the context



Other methods e.g. using proxies such as

Mouse clicks

• The number of mouse clicks increases

during frustrating episodes (Scheirer et al., 2002)


Measures / questionnaires (self-report)

MAACL: Multiple Affect Adjective Checklist (Zuckerman & Lubin, 1965)

• One of the first self-report measures, measures a combination of anxiety, depression, and hostility

POMS: Profile of Mood States (McNair, Lorr, & Droppleman, 1971)

• Probably the most frequently used measures of mood psychology

• Six mood states: tension, depression, anger, vigor, fatigue, and confusion.

PANAS: Positive and Negative Affect Schedule (Watson, Clark, & Tellegen, 1988)

• Widely used in different disciplines

• Measures a mixture of emotions, moods, and affects.

AD ACL: Activation Deactivation Adjective Checklist (Thayer, 1989)

EFI: Exercise-Induced Feeling Inventory (Gauvin & Rejeski, 1993)

List from Ekkekakis (2012)


The study on filtering, emotion and HIB


Emotions and internet filtering

Internet filtering (website blocking or Internet censorship) is a mechanism designed to control online activity through filtering and blocking of particular parts or features of the Internet such as websites, search words, or online communities (Eriksson and Giacomello, 2009, p. 207).

Used in many countries for various reasons

• At organisation level: public libraries and hospitals• Filtering wireless (Wi-Fi) Internet access in public places(Spacey et al.,

2017) (UK)

• At national level: for political, religious and ideological reasons


http://Peyvandha.ir

http://peyvandha.ir/


Peyvandha.ir on Alexa.com


Aims

Find out about the relationship between internet filtering, emotions and information seeking behaviour

• Identify the ways by which students overcome internet filtering

• Know the emotions they feel when they face internet filtering

• To find out about the impact of internet filtering on information-seeking behaviour, and the changes it might cause in their behaviour


Past studies

• No study on filtering & emotion, or filtering and HIB

• China, survey, Chinese web users bypassed the firewall in China mainly for information and socializing. (Yang and Liu, 2014)

• Pakistan, log analysis, blocking websites impacted on users’ behaviour; it caused a major shift towards increased encrypted traffic which means users used censorship-bypass mechanisms to directly access the content. (Khattak et al., 2014)


Method

• Fifteen participants, postgraduate

students in social sciences, Iran

• 4 tasks to complete; tasks specifically

chosen so their search results would

include blocked items (e.g. looking for

biography and samples of works of journalist X)

• Think aloud during search sessions

• Questionnaire and interview after search


Findings - emotions

• Facing filtering causes disgust, sadness, anger, and curiosity

• Finding information results in positive emotions, feeling good, happy, proud and pleased

• Main reason for negative emotions is not being unable to access information, but feeling not having freedom and being controlled


Findings - relations

• More curious, more determined to continue the search for the information.

• The stronger the feeling of not having freedom and being controlled : the more cautious in taking actions to overcome filtering

• Feeling more despair : more likely to give up searching


Findings – encountering filtering

• Using anti-filter software• Psiphon, Freegate, UltraSurf, Tor Browser; VPN

• Modifying search strategy• Using synonyms or specialized terms

• Giving up searching and using other resources


Findings – changes in behaviour

Users use a variety of methods to bypass filtering (mostly by using anti-filter software)

Filtering

• Encourages users to use channels such as social networking services (SNS) to share resources

• Increases the use of library material by some of the users

• Makes users more likely to visit more pages of results and click on more hits in the results, unlike users who do not experience filtering who rarely go past the first page

• Stimulates their curiosity and they become more determined to access the content


ReferencesBrave, S., Hutchinson, K. & Nass, C. (2005). Computers that care: investigating the effects of orientation of emotion exhibited by an embodied

computer agent. International Journal of Human-Computer Studies, 62(2), 161-178.

Dervin, B., & Reinhard, C.D. (2007). How emotional dimensions of situated information seeking related to user evaluations of help from sources:

an exemplar study informed by sense-making methodology, pp. 51-84 in Nahld, D., & Bilal, D. (eds). Information and emotion: the

emergent affective paradigm in information behavior research and theory, Medford (NJ): Information Today.

Ekkekakis, P. (2012). Affect, mood, and emotion, pp. 321-332 in Tenenbaum, G., Eklund, E., & Kamata, A. (Eds). Measurement in sport and

exercise psychology, Champaign (IL): Human Kinetics.

Eriksson, J., & Giacomello, G. (2009). Who controls what, and under what conditions?. International Studies Review, 11(1), 206–210.

Gauvin, L., & Rejeski, W.J. (1993). The Exercise-Induced Feeling Inventory: Development and initial validation. Journal of Sport and Exercise Psychology, 15,

403-423.

Gwizdka, J., & Lopatovska, I. (2009). The Role of Subjective Factors in the Information Search Process. Journal of the American Society for

Information Science and Technology, 60(12), 2452–2464.

Kleinginna, P. R., & Kleinginna, A. M. (1981). A categorized list of emotion definitions, with suggestions for a consensual definition. Motivation

and Emotion, 5(4), 345-379.

Khattak, S., Javed, M., Khayam, S.A., Uzmi, Z.A. and Paxson, V. (2014, November). A look at the consequences of internet censorship through

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References - continuedNahl, D., Bilal, D., Druin, A., & Fisher, K. (2005). Emotional design II: Affective information behavior research with adult and child populations.

Proceedings of the Association for Information Science and Technology, 42(1).

Norman, D. A. (2004). Emotional design: Why we love (or hate) everyday things. Basic Civitas Books.

Onwuegbuzie, A. J., Jiao, Q. G., & Bostick, S. L. (2004). Library anxiety: Theory, research, and applications. Scarecrow Press.

Picard, R. W., & Picard, R. (1997). Affective computing (Vol. 252). Cambridge: MIT press.

Spacey, R., Muir, A., Cooke, L., Creaser, C. ,& Spezi, V. (2017). Filtering wireless (Wi-Fi) Internet access in public places. Journal of

Librarianship and Information Science, 49(1), 15-25.

Robbins,, S.P., &, Judge, T.A. (2012). Emotions and moods. Organizational behavior, Pearson.

Scheirer, J., Fernandez, R., Klein, J., & Picard, R. W. (2002). Frustrating the user on purpose: a step toward building an affective computer.

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Tenopir, C., Wang, P., Zhang, Y., Simmons, B., & Pollard, R. (2008). Academic users’ interactions with ScienceDirect in search tasks: Affective

and cognitive behaviors. Information Processing & Management, 44(1), 105-121.

Thayer, RE. (1989). The biopsychology of mood and arousal. New York: Oxford University Press.

Tinto, F., & Ruthven, I. (2016). Sharing “happy” information. Journal of the Association for Information Science and Technology, 67(10), 2329-2343.

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and learning via the internet. Political Psychology, 29(2), 247-273.

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Computers in Human Behavior, 37, 249-257

Zuckerman, M., & Lubin, B. (1965). Manual for the Multiple Affect Adjective Check List. San Diego: Educational and Industrial Testing Service.

information behaviour and emotions · 2017-09-07 · school of information studies why study...

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