ieee transactions on affective computing, vol. 5, no. 2 ... · such as a “feeling of hunger” or...

Are They Different? Affect, Feeling, Emotion,Sentiment, and Opinion Detection in TextMyriam Munezero, Calkin Suero Montero,Member, IEEE, Erkki Sutinen, and John Pajunen

Abstract—A major limitation in the automatic detection of affect, feelings, emotions, sentiments, and opinions in text is the lack of

proper differentiation between these subjective terms and understanding of how they relate to one another. This lack of differentiation

not only leads to inconsistency in terminology usage but also makes the subtleties and nuances expressed by the five terms difficult to

understand, resulting in subpar detection of the terms in text. In light of such limitation, this paper clarifies the differences between

these five subjective terms and reveals significant concepts to the computational linguistics community for their effective detection and

processing in text.

Index Terms—Affect sensing and analysis, computation models of emotion

Ç

1 INTRODUCTION

THE ability to accurately identify and reflect “what is sub-jectively written” is valuable. This ability influences

real-world text analysis applications such as targeting mar-keting campaigns to users with specific likes and dislikes oridentifying online antisocial behavior, for example, cyber-bullying. Thus, being able to understand and detect the sub-jective nuances in text is valuable for its actual applications.

Affect, feeling, emotion, sentiment, and opinion areterms relating to human subjectivity. Because subjectivity isa feature of a person’s mind, it “is not open to objectiveobservation or verification” [1]. Subjective experiences arecreated from the subject perspective, and they reflect thesubject’s desires, beliefs and feelings. Thus, the detection ofsubjectivity is a difficult natural language processing (NLP)task yet intriguing as a research endeavour.

Current text-based subjectivity detection efforts, how-ever, are limited in their detection abilities. For instance,most of the sentiment analysis (SA) and opinion mining(OM) studies have been focused on detecting text polarity(positive, negative, and neutral) [2]. However, sentimentsand opinions are more complex than just having polarity.Moreover, subjectivity terms indicating affects, feelings,emotions, sentiments, and opinions in text are often under-stood similarly and used interchangeably in NLP researchwithout sufficient differentiation between them. This lack ofconsistency in terminology usage leads to poor apprehen-sion and confusion about what concepts or features shouldbe involved in the text analysis, as also noted by Hovy [3],Balahur et al. [4] and Alm [5].

Thus, to overcome the outlined limitations, we went astep further and clearly established a distinction betweenthe different branches of the subjectivity terms. Althoughthere are similarities, subjectivity detection advancestoward more fine-grained analysis of human subjectivity,compelling the subjectivity terms’ subtle differences to playan important role in increasing the effectiveness of NLPdetection methods.

To reach their full potential, the NLP analysis must beable to capture the subtle differences that reflect personal,cultural, and societal signals within the subjectivity terms.Therefore, it is fundamental to establish concise and clearterminologies. In this paper, we aimed to shed light on thedifferences among subjectivity terms and put forwardthe potential that these differences provide to advancing theNLP research.

2 SUBJECTIVITY TERMS

Standard dictionaries are an initial resource with which toanalyze the meanings of words. Table 1 provides the defini-tions of affect, feeling, emotion, sentiment, and opinionalong with their synonyms, based on the Merriam-WebsterOnline Dictionary [6].

From the definitions and the synonyms given in Table 1,the source of confusion in meaning and usage is shownby the repetition of the shared synonyms. The confusion isfurther compounded by the common everyday usage of theterms [7]. For example, when a person says “my sentimentsexactly!” it often has the same meaning as “my feelingsexactly!” Thus, the subtle differences as they are used inresearch literature will be revealed only by diving deeperinto the definitions of the above terms. Moreover, it willalso be possible to model or detect the subjective terms asthey exist by outlining the differences.

3 SUBJECTIVITY TERMS IN THE PSYCHOLOGICAL

LITERATURE

3.1 Affects

Among all of the subjectivity terms, affect seems to be themost abstract and difficult to be fully realized in language

The beginning of wisdom is the definition of terms.—Socrates

� M. D. Munezero, C. Suero Montero, and E. Sutinen is with the School ofComputing, University of Eastern Finland, PL 111, 80101 Joensuu,Finland. E-mail: {myriam.munezero, calkin.montero, erkki.sutinen}@uef.fi.

� J. Pajunen is with the Department of Philosophy, University of Jyv€askyl€a,Seminaarinkatu 15, 40014, Jyv€askyl€a, Finland.E-mail: [email protected].

Manuscript received 23 June 2013; revised 13 Feb. 2014; accepted 2 Apr. 2014.Date of publication 13 Apr. 2014; date of current version 23 July 2014.Recommended for acceptance by R. Mihalcea.For information on obtaining reprints of this article, please send e-mail to:[email protected], and reference the Digital Object Identifier below.Digital Object Identifier no. 10.1109/TAFFC.2014.2317187

IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, VOL. 5, NO. 2, APRIL-JUNE 2014 101

1949-3045� 2014 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

as it is always prior to or outside of consciousness [8]. Affectis the “body’s way of preparing itself for action in a givencircumstance by adding a quantitative dimension of inten-sity to the quality of an experience” [9]. Affect within thepsychological literature has been thought of as the umbrellaterm; it subsumes emotions, feelings, and sentiments [10].Batson et al. [11] found affect to be the most general of theterms, describing it as more phylogenetically and ontologe-netically primitive than emotions and further explainingthat “affect is present in the yelp of a dog and in the coo orcry of an infant.” Shouse [9] defined affect as a “non-con-scious experience of intensity: as a moment of unformedand unstructured potential.” He adds that affect “plays animportant role in determining the relationship between ourbodies, our environment, and others.” Thus, affect can bedefined as positive and negative evaluations of an object,behavior, or idea with intensity and activity dimensions[12]. Zajonc [13] similarly agreed that affect reveals prefer-ences; that is, it informs the organism experiencing it aboutthose states of affairs that it values more than others.Change from a less valued to a more valued state is

associated with positive affect; change from a more valuedto a less valued state is associated with negative affect. Theintensity of the affect then reveals the magnitude of thevalue preference [11].

3.2 Feelings

Shouse [9] defined a feeling as a “sensation that has beenchecked against previous experiences and labeled.” It is per-sonal and biographical because every person has a distinctset of previous sensations from which to draw from wheninterpreting and labelling their feelings.” Shouse made aninteresting distinction between feelings and affect in infants,in that infants do not experience feelings because they lackboth language and biography. He said that what infantsexperience is affect. Moreover, Thoits [12] stated that feel-ings are the experience of physical drive states such as hun-ger, pain, fatigue, and emotional states. They are part of our“psychological and physical baggage” [10]. Friedenbergand Silverman [14] added that feelings “correspond to thesubjective experience of an emotion.” Wierzbicka [15] con-firmed this by stating that “feelings are subjective, and theyappear to be universally thought of as related in some casesto what is happening in the body; but they are also oftenthought of as based on certain recurrent thoughts—cogni-tive scenarios shaped by the particular culture.” Wierzbicka[15] additionally pointed out that the concept of feelings isuniversal—“all languages appear to have a word for theconcept ‘feel,’ we can assume that this concept is an integralpart of the universal folk model of a person, that is, that inall cultures people attribute feels to other people as well asto themselves. Furthermore, evidence suggests that in allcultures people distinguish linguistically (and in particular,lexically) between different kinds of feelings.” In this work,we do not consider feelings that are not thought related,such as a “feeling of hunger” or a “feeling of cold,” as it isnot comparable with the other affect terms. It is clear thatone will not talk about an affect, an emotion, a sentiment oran opinion of hunger, cold, and so on [15].

3.3 Emotions

Definitions of emotions in the literature have been manyand varied. Kleinginna and Kleinginna [16] performed acompilation of 92 definitions and nine skeptical statementsfrom a variety of emotion literature sources. On the basis oftheir compilation, they suggested a formal definition ofemotion as “a complex set of interactions among subjectiveand objective factors, mediated by neural and hormonal sys-tems, which can a) give rise to affective experiences such asfeelings of arousal, pleasure and displeasure; b) generatecognitive processes such as emotionally relevant perceptualaffect, appraisals, labeling processes; c) active widespreadphysiological adjustments to the arousing conditions; andd) lead to behavior that is often, but not always expressive,goal-directed and adaptive.”

In his work on emotion psychology, Scherer [7] blamedthe confusion in the definition of emotions to the failure toclearly distinguish between the different classes of phenom-ena. Scherer advised that the general affective valence orpreference should not be treated in the same manner asemotional episodes, nor should it be to the more enduring

TABLE 1Definitions Provided by Merriam-Webster Online Dictionary [6]

102 IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, VOL. 5, NO. 2, APRIL-JUNE 2014

affective states such as attitudes. However, emotions as atype of affective state do have valence and intensity [11].Scherer settled on a working definition of emotion as“episodes of coordinated changes in several components(including at least neurophysiological activation, motorexpression and subjective feeling but possibly also actiontendencies and cognitive processes) in response to externalor internal events of major significance to the organism.”Thoits [12] defined emotions as culturally determined typesof feelings or affect. Shouse [9] rephrased to say that emo-tions are the projections or display of a feeling, and unlikefeelings, the display of emotions can be genuine or feigned.Shouse adds that we “broadcast emotion to the world;sometimes that broadcast is an expression of our internalstate and other times it is contrived in order to fulfill socialexpectation.” Dolan [17] believed that from a psychologicalperspective, emotions have three characteristics: “firstunlike thoughts, emotions are embodied, that is we experi-ence emotions not just as mental events that are in our headsbut also as full-body experiences. Secondly, unlike cogni-tion, emotions are harder to control. We may find that it iseasier to change our thoughts than our emotions. Thirdly,emotions seem less encapsulated than thoughts; that is theyseem to have a more global impact on our behavior.” Batsonet al. [11] further described emotions as reflections of the“existence of a specific goal or of perceived change in one’srelationship to a specific goal in the present.” Goals, asBatson pointed out, reflect values, and what is valueddepends on an individual’s current situation, which drawsfrom personal experiences, culture, and society.

Friedenberg and Silverman [14] simply considered emo-tion as “brief brain and body episode that facilitates aresponse to a significant event.” Continuing from Shouse’sexample, infants display emotions although they do nothave the biography or the language skills to experience feel-ings. The emotions of an infant are direct expressions ofaffect. Thus, according to Shouse [9], emotions are theexpression of affect and/or feelings

3.4 Sentiments

Sentiments are defined by Cattell [18] as “an acquired andrelatively permanent major neuropsychic disposition toreact emotionally, cognitively, and conatively toward a cer-tain object (or situation) in a certain stable fashion, withawareness of the object and the manner of reacting.” Gor-don [19] has a similar definition; sentiments are “sociallyconstructed patterns of sensations, expressive gestures, andcultural meanings organized around a relationship to asocial object, usually another person (. . .) or group such as afamily.” Similarly, Murray and Morgan [20] defined senti-ment as “a more or less enduring disposition (predilectionor readiness) in a personality to respond with a positive ornegative affect to a specified entity.”

Cattell [18] further pointed out that the “functioning ofsentiments is accompanied in the individual by interest anda sense, on his part, of ‘values’ in the object.” Thus, theobject has come to possess more or less an enduring powerto “evoke relatively intense and frequent reactions, positiveor negative in a person” [20]. Broad [21] explained that asentiment is formed when a certain object is constantly per-ceived or thought of by a person and, over time, the person

creates a dispositional idea toward the object. This disposi-tional idea has corresponding emotional tendencies that areevoked whenever the person perceives and thinks about theobject or any symbols related to the object.

Examples of sentiments include romantic love, parentallove, loyalty, friendship, patriotism, hate, as well as moretransient, acute emotional responses, to social losses (sor-row, envy) and gains (pride, gratitude) [12].

3.5 Opinions

Opinions in research have been synonymous to what a per-son is thinking. An opinion is the idea or knowledge onehas about something. In Pang and Lee’s work [2], an opin-ion “implies a conclusion thought out yet open to dispute”;that is, experts on a topic can have very different opinions,which they might change in light of new evidence. Psycho-analysts describe opinions as rationalizations, explanations,and justifications [22].

Young [22] further defined an opinion as a judgementbased on grounds insufficient to produce certainty. Thus,opinions leave room for error in thought. Young [22] charac-terizes opinions as provisional convictions, views held asprobable, or a belief or disbelief in some idea or form of con-duct. Beliefs, as Fishbein and Ajzen [23] described, are the“the subjects perception that an object or person has certaincharacteristics, qualities, or attributes, or is related to someother concept, object, or person.”

According to Kim and Hovy [24], an opinion consists ofthe following four parts: topic, opinion holder, claim, andsentiment. That is, for each opinion, there is a holder whobelieves a claim about a topic and then associates a positive,negative, or neutral (neutral here does not mean absence,e.g., “The winter has arrived. It is not good or bad, justsaying”) sentiment with the claim. Fig. 1 illustrates how thefour aspects can appear in a sentence. Kim and Hovy [24]further pointed out that an opinion can be subjectivewithout implying a sentiment. This was also acknowledgedby Sokolova and Bobicev [25], who defined opinionsas “subjective statements that may or may not implyemotions.”

Liu [26] rather used a mathematical representation of anopinion as a quintuple <o; f; so; h; t> , where o is an object;f is a feature of the object o; so is the orientation or polarityof the opinion on feature f of object o (positive, negative orneutral); h is an opinion holder; t is the time when the opin-ion is expressed.

4 DIFFERENTIATING FACTORS OF SUBJECTIVITY

TERMS

4.1 Affects, Feelings, and Emotions

Massumi [27], in his “Notes on the Translation andAcknowledgement,” saw affect as “prepersonal”; that is,

Fig. 1. Example of an opinion (based on Kim and Hovy [24]).

MUNEZERO ET AL.: ARE THEY DIFFERENT? AFFECT, FEELING, EMOTION, SENTIMENT, AND OPINION DETECTION IN TEXT 103

affect exists outside of consciousness before personal self-awareness develops. Shouse [9] further expands this ideaby giving the example of affective expression in infantswhen the expression of feelings is not yet developed. Fur-thermore, Matthis [28] defined affect as an “affective matrixlinked to a predisposition of the bodily systems to react in acertain way to internal or external stimuli” and also as a“higher-order category under which both feelings and emo-tions fall.”

In contrast, feelings are seen more tangibly as a “broadcategory of person-centered psycho-physiologicalsensations” [29] in [30], as “affective phenomena to whichwe have direct conscious access” [28], and as labeled sen-sations, “personal and biographical” [9].

Emotions are seen as preconscious phenomena; that is,they are capable of becoming conscious upon recall. Emo-tions are defined based on the expression of feelings as a“subset of particularly visible and identifiable feelings” [29]in [30]; as “affective manifestations to which we do not havedirect conscious access, but which can be inferred frombehavioural clues” [28]; and as a “social . . . projection/dis-play of a feeling” [9]. Furthermore, Wierzbicka [15] notedthe influence of culture on emotions and stated thatalthough “feeling is universal and can be safely used in theinvestigation of human experience and human nature, theconcept of emotion is culture-bound and cannot be similarlyrelied on.” Therefore, the way in which emotionsare expressed is more often than not a result of the culture/society one lives in.

We, thus, find differentiating factors between affect, feel-ings, and emotions, as follows:

� Affect is, in fact, a predecessor to feelings andemotions.

� Feelings are person-centered, conscious phenomena.

� Emotions are preconscious social expressions of feel-ings and affect influenced by culture.

4.2 Sentiments and Emotions

The concepts of emotions and sentiments have oftenbeen used interchangeably. This is mostly because bothemotions and sentiments refer to “experiences that resultfrom the combined influences of the biological, the cog-nitive, and the social” [31]. However, sentiments are dif-ferentiated from emotions by the duration in which theyare experienced.

Although emotions are brief episodes of brain, auto-nomic, and behavioral changes [32], sentiments havebeen found to form and be held for a longer period. Sen-timents, in addition, are more stable and dispositionalthan emotions [33]. BenZe’ev [33] further explained thata person may have a sentiment of, for example, lovewhen he or she does not actually have an occurring stateof love.

Moreover, sentiments are formed and directed toward anobject1, whereas emotions are not always targeted towardan object. For instance, one can wake up feeling depressedor happy for no apparent reason [34].

4.3 Sentiments and Opinions

Sentiments and opinions have also been used interchange-ably, perhaps because most NLP research on opinions hasfocused on detecting their subjective part, which has beenreferred to as sentiment (see Kim and Hovy [24]). How-ever, opinions are personal interpretations of informationformed in the mind and not necessarily constrained bysocial expectations, whereas sentiments are generallysocially constructed. In addition, opinions are prominentlybased on objective and/or subjective probabilities of infor-mation about a topic, whereas sentiments are prompted byemotions.

Cattell [18] distinguished between sentiments and opin-ions in his analysis by pointing out that an individual pos-sesses a sentiment and experiences a complex secondary orderived emotion, whereas an opinion is not possessed but isan expression of personal interpretation of information.Sokolova and Lapalme [35] acknowledged that sentimentsshould not be treated as identical to opinions because opin-ions can be expressed about a fact of matter, in a descriptiveand assessing way, without the expressions being emotion-ally charged [36].

Hence, we find differentiating factors between senti-ments and opinions, as follows:

� Sentiments are partly social constructs of emotionsthat develop over time and are enduring.

� Opinions are personal interpretations of informationthat may or may not be emotionally charged.

Fig. 2 serves to illustrate the differentiating factors of thesubjective terms.

5 ADVANCING THE DETECTION OF SUBJECTIVITY

TERMS IN TEXT

From the definitions of the terms, we observe that the cur-rent NLP approaches will benefit from a deeper analysis of

Fig. 2. Differentiating factors between affect, feelings, emotions, senti-ments and opinions.

1. An object refers to a person, a thing, a condition, a place or anevent at which a mental state is directed [34].


affect, feelings, emotions, sentiments and opinions in text. Inour attempt to expand the detection approaches of theseterms in text, we put forward how the differentiating factorswe identified in Section 4 should be realized and applied bybuilding on the current NLP advances.

5.1 Detecting Affect

Affective computing (AC) as introduced by Picard [37], isa broader research field concerned with giving computersthe ability to recognize, express, and, in some cases,“have” emotions and other related affective phenomena.AC explores the recognition of affect in faces, voice, pos-ture, or other mannerisms and behaviors as a multimodalresearch field.

In Picard’s [37] work on AC, the terms emotion and affectare used interchangeably. This is quite understandablebecause, as we have seen, emotions are in fact expressionsof affect. However, as already discussed, affect is difficult torealize in language. Conversely, when we perceive theworld around, we primitively have an affective reaction(good or bad) [13] to the objects in it. That is, we perceiveobjects to be beautiful, ugly, awful, and so on. These affec-tive reactions are the conscious representation of affect,which in language is expressed through feelings andemotions.

5.2 Detecting Feelings and Emotions

Unlike affect, emotions and feelings have been affirmed byseveral researchers as being expressible in language ([38],[39], [40], [41]). However, because of its complexity, emo-tions are not always fully accessible in written language. Inthis section, we look at both emotions and feelings as emo-tions are expressions of feelings (see Fig. 2).

From the definitions of emotion we considered inSection 2, particularly in the summary of Kleinginna andKleinginna’s [16] study, we find that there seems to be a rea-sonable agreement over the following relevant factors thatdetermine an emotion:

a) Appraisal (cognition).b) Physiological reactions of the body, such as

increased heartbeat and sweating.c) Feeling.d) Expressive display, such as facial expression and

bodily expression.e) Readiness to behave in a particular way (also called

action tendencies by Frijda [42]).These five factors of emotion are not independent of

one another, and in fact, changes in one factor can leaddirectly to the corresponding changes in others. How-ever, it is not certain which factor precedes which, or ifall the factors are necessary during an emotional experi-ence [43]. Nevertheless, Russell and Barrett [34] pointedout that the fewer factors assessed, the less convincingthe results. Furthermore, these factors are also influencedby culture and societal norms. Culture and society areidentified here as fundamental parts of emotion expres-sion because emotions are culturally/socially constrainedexpressions of affect. Hence, social processes and culturalnorms play a significant role in specifying how weexpress emotions [44].

However, Mesquita and Leu [45], in their cultural psy-chology of emotion research, acknowledged the possibilityof some aspects of emotions, for example, facial expressionsand other physiological reactions, to be hardwired and com-mon across cultures. Nevertheless, they also put forwardthat there are cultural differences in each of the above men-tioned five factors of emotion. As an example, Mesquita andLeu [45] found insults were appraised as an honor violationand were more likely to result in anger and aggressiveresponses in the south than in the north of the United Stateswhere honor culture is not strong.

The identification and assessment of some or all of thefactors would provide a better analysis of emotions intext. Conati [46], for example, combined evidence fromappraisals that produce emotions and bodily expressionsassociated with emotion expression for his analysis ofemotional experiences during learning. However, thereare limitations incurred with text environments in thatthey cannot deliver a full emotional experience by them-selves [47]. That is, it is not possible to access or measuredirectly the physiological changes in the body of thewriter through text, for instance. Regardless, it is possi-ble for all the five factors to be expressed in language tosome extent.

5.2.1 A Scenario

To illustrate how the emotional experience factors could belexically encoded in text to communicate an emotion thatcould be labeled as anger,2 let us consider a hypotheticalscenario where a friend communicates an event to anotherfriend.

“Hi John, remember my friend Luke? Can you believe that hepunched me on Friday at John’s party! I can’t believe my friendwould hit me, he was acting crazy. Never felt so insulted in mylife. How could he do that!!! Just made me lose my temper. Iwanted to just hit him right back too, could feel the adrenalinerushing in. Started swearing at him and pointing a certain fingerto him. You should have been there. Wanted to kick the guy’s a��,but I thought it was not was not worth it you know.”

From the story we can observe the following emotionfactors:

- Appraisal—“I can’t believe my friend hit me, he wascrazy”

� This expression is the appraisal of the elicitingevent, which is assessed as negative and unde-sirable to one’s social interaction and well-being. Appraisals are evident in text throughthe use of evaluative language (for identifyingexpressions of appraisal in text, see Read et al.[49]). Appraisals in text can be used as evidenceof an emotion.

- Physiological reaction—“adrenaline rushing in”

� Certain phrases can be used to express the innerphysiological arousal. References to heart rate

2. Frijda [48] explained that “anger, in English, tends to focus oneither the appraisal that someone else was doing something unpleasantwhich was not felt to be in line with accepted rules or on the impulse tooppose and counteragress.”


(my heart skipped a beat), temperature (gettingcold feet), muscles tightening (knots or butterfliesin the stomach), breathing (finding it hard tobreath), and so on.

- A (negative) feeling—“made me loose my temper”

� Feelings are made clear using descriptive orexpressive language. They can be explicitly statedwith emotion labels such as “angry” or “furious”,or they could be expressed implicitly “made melose my temper”.

- Expressive display—“swearing at him and pointing acertain finger to him”

� Expressive behavior such as facial expressions canbe found in text in the use of emblems, such asemoticons (e.g., ) and with references to gesturesand postures (e.g., shaking one’s head in disap-proval, fiddling, clearing of throat, quivering,grin stretching from ear to ear).3

- Readiness to behave in a particular way—“wanted tojust hit him right back”

� Behaviors are expressed using verbs (e.g., “hit”).As can be seen in this scenario, beyond the use of emo-

tion-bearing words, an author is equipped with a variety oflinguistic markers and their combinations to convey anemotion [50]. These markers include stylistic features suchas punctuations and capitalization [51]. For emotion detec-tion, it is particularly important to go beyond word-levelanalysis, as single words by themselves are not able to carryall the emotional information: emotions are often hiddenbehind combinations of words [52].

5.2.2 Labeling Emotions as Shaped by Culture

and Society

Of interest to NLP is being able to tell which emotion isexpressed in the text. Predominantly, research on detectingemotions from text has focused on capturing emotion wordsbased on three emotion models, that is, categories of basicemotions [53], emotion dimensions [54], or cognitive-appraisal categories [55]. These models differ greatly withrespect to the number of emotions they explain as well asthe principles that they evoked [7]. Unfortunately, as ofdate, no general model of emotions has yet been agreed on[56]. It is not the aim of this paper to argue on the correctmodel to use in labeling emotions in text because they areall founded on different psychological theories of emotion,and they all fit specific purposes according to the goals andpurpose of a particular research in various fields.

In computational linguistics, attempts at detecting emo-tions have been made using lexical resources such as Word-NetAffect [57] to mark the presence of emotion-bearingwords in text or Affective Norms for English Words(ANEW) [58] to mark words with normative emotional rat-ings. Also, commonsense knowledge bases such as Emoti-Net [59] have been used to capture emotions in texts that donot have emotion-bearing words.

Central to this paper is the call to extend the NLPapproaches to include the analysis of words, sentences, ordocuments on a cultural level. This is because naturallythe choice of words and their intended meaning are per-sonally, contextually, culturally, and socially dependent.That is, a word, a phrase, or a sentence might have oneemotional value when considered in isolation, but whenevaluated on a cultural or societal context, the emotionalvalue might change. An example of this can be observedin the following sentence: “That ride is wicked.” By defi-nition of the word “wicked”, the sentence has an unpleas-ant connotation in some communities; however, thesentence would be associated with pleasantness in somecommunities such as the United Kingdom. Similarly, theword “blue” was observed by Das [60] in their work asbeing positive in many countries but was seen as negativearound the Middle Eastern region. Das [60] illustrated thepossibility of encoding cultural information in lexicalresources to create a more robust resource for emotiondetection.

Thus, regardless of the model chosen to represent theemotions (e.g., Ekman’s six basic emotions [53] orRussell’s dimensions [54]) or the approach used, theresearcher should also evaluate a writer’s emotional expe-rience on a cultural, societal level. This could be doneprimitively by accessing the location information of theanalyzed text. In the case of online sources, for instance,Facebook [61], it is possible to access the location4 ornationality information of a user whenever that informa-tion is made public. Hence, investigations of automaticdetection of emotions have the means to deploy a widerethnographic inquiry into the words used to express emo-tions. Fig. 3 summarizes the proposed structure for analy-sis for emotions from text.5

Fig. 3. Schematic structure of an emotion.

3. We must keep in mind, however, that the same expressive behav-ior might indicate a different emotional experience, for example, cryingwhen feeling happy or sad.

4. Here it is supposed that the location where the text is generatedcorresponds to the physical world where the writer is and, hence, mayprovide clues on his country or society.

5. However, one must also be careful and keep in mind that what isexpressed might not be what is experienced. For example someone say-ing “I hate you” might just be saying it as a joke and not be reallyexperiencing the emotion “hate”.


5.3 Detecting Sentiments

Expressions of Sentiment, by default, have almost beendefined in NLP as a positive or negative expression. How-ever, from our analysis, they are a more complex phenome-non. Sentiments involve emotional dispositions formedtoward an object, and unlike emotions which are brief, sen-timents about an object are enduring. Thus, labeling briefemotional episodes or affective qualities as sentiments is amisrepresentation.

5.3.1 Sentiment Endurance

French [62] pointed out that increasing experience with anobject “brings about differentiation of aspects of both posi-tive and negative valence and in this turn leads to consciousambitendency.” Shelly [63] also acknowledged thatincreased experience with an object leads to enduring pat-terns conceptualized as liking and disliking toward theobject. These two broad categories of like and dislike aresufficient enough to include both positive and negativeemotions that may arise whenever the liked or dislikedobject comes to mind.

Approaching sentiments as enduring is useful forresearch in domains such as terrorism or antisocial behavior,as they indicate dispositions that are not about to changeunless something intervenes. It could also provide betterinformed reviews; that is, it could assist in judging the rele-vancy or impact of reviews. A bad review of the movie SkyFall from a person who generally enjoys and likes actionmovies, for instance, would probably have more relevancefor recommendation systems than a bad review from some-one who does not have a liking for action movies. Fig. 4illustrates our formulation of the structure of a sentiment.

However, the field dedicated to detecting sentiments, SA,has not treated sentiments as enduring. Realistically, senti-ments can only be inferred on the basis of the regular occur-rence of emotional responses to an object [62]. As anexperiment, we made efforts to infer enduring sentimentsbased on emotions. The method was practical enough toallow us to collect freely available user data from Twitterover a period ranging from three months to one year,depending on the user. The user’s tweets were gatheredand filtered according to an object (e.g., person, place, andsituation). With the filtered tweets, we analyzed the emo-tions along Plutchik’s eight basic emotions [64]: joy trust,anticipation, surprise, anger, fear, disgust, and sadness.

These emotions were then mapped into two broad cate-gories: like and dislike. Finally, a total score of like and dislikewas calculated over the period of the tweets as a function ofthe emotions present in the texts. This approach allowed usto visualize the user’s regularly occurring dispositionstoward the object in a certain period6 [65]. The advantage ofapproaching sentiments in this manner is that the emotionaldisposition formed toward an object can be observed along-side the comments made by a user. Such information is use-ful, for instance, in computing the loyalty of customerstoward a product. For example, looking at tweets made by auser, we are able to see that the person dislikes the iPhone5but likes the new iPad and, overall the brand Apple.

5.4 Detecting Opinions

In computational linguistics and NLP, the field dedicated tothe research and detection of opinions in text is called opin-ion mining. As mentioned previously, the terms OM and SAhave often been used interchangeably, but as illustrated inFig. 2, opinions can be based on the personal interpretationof information but may not carry a sentiment or an emo-tion.7 Thus, with the definition of sentiment as discussed inSections 2 and 3, it would be misleading for NLP research-ers to treat the concepts as the same.

From the definitions of opinions, we find that an opinionincludes at least three parts: topic, opinion holder, andclaim. In addition, an opinion may include the following:(1) an emotional and sentimental expression, (2) feature(s)of the topic, and (3) time (the time that an opinion is made).

Particularly of interest to OM is to determine whetherthe expressed opinions are positive, negative, or neutral.An opinion can be categorized as neutral when it is statedas a matter of fact without any positive or negative evalu-ation, for example, “Bin Laden is hiding in Pakistan”.8

Moreover, if an opinion includes an emotion or sentimentexpression, then the expressed emotions can be used todetermine the polarity of the opinion as negative or posi-tive. In the case that no emotion or sentiment is attached,the polarity of an opinion can still be determined in twoways, as follows:

1. By analyzing if there is an affective reaction asso-ciated to the topic or feature (“I found this bookboring” vs. “this movie was directed beautifully”).

Fig. 4. Schematic structure of a sentiment.

6. We acknowledge that outside of twitter and diaries, it is notalways possible to find one person’s thoughts and emotional disposi-tions toward an object over a long period for analysis.

7. Note that we used a sentiment or an emotion. This is because aperson might form an opinion based on a brief emotional experience(“I loved that movie”, just after coming from the cinema) or based on adisposition they have had (“Action movies are the best”, based on theliking disposition a person has developed for action movies). Unfortu-nately, in many domains where OM is applied, for example, product orcustomer reviews, the brief versus enduring distinction is not easy toobtain.

8. Sayeed [66] pointed out that the polarity of an opinion is depen-dent on the perspective of the reader of the text. For example, to acasual reader, the sentence “Bin Laden is hiding in Pakistan” might beperceived as a neutral sentence, but to an interested reader, it mightrepresent a positive or a negative statement depending on whetherknowing the location of Bin Laden is a good thing or not. However, werestricted our analysis of the subjective terms from the perspective ofthe author.


Research on the polarity of opinions based on theaffectively charged reactions on a topic has beenperformed using current NLP approaches, forinstance, using of affective keywords from exist-ing knowledge bases (WordNet [67]) or from pur-pose built lexicons based on domain-dependentcorpora ([68], [69], [70], [71]).

2. By analyzing the words people choose to describetheir experiences. There are many instances wherean author expresses an opinion without attachingany positive or negative affectively charged words(e.g., “the computer battery only last three hours”).These instances are more challenging to categorizeas positive or negative as they require a large bodyof knowledge, but their categorization is not impos-sible. Taking the above statement as an example,“The computer battery only last three hours,” theword “only” is characterized by Sokolova andLapalme [35] as a descriptive word. Depending onthe context, the word “only” can serve as a hint forboth a positive and a negative opinion. In our exam-ple, it indicates that the user of the computerexpected the battery to last longer. Thus, the wholestatement can be categorized as a negative opinion.Unlike lists of affectively charged words that work atword-level, the analysis of descriptive wordsrequires a wider context, such as a whole sentence, awhole paragraph, or whole text. The analysis ofdescriptive words is also dependent on the topic ofthe text [35].

Thus, equipped with the knowledge of how opinionsare differentiated from the other subjective terms, we for-mulate a schematic structure of an opinion that can guidefuture research in OM, as shown in Fig. 5. However, thisstructure does not describe opinions expressed as sar-casm or irony in which for instance, a seemingly positiveopinion communicates the opposite of what is expressed(e.g., “It’s not that there isn’t anything positive to sayabout the field. There is. After 92 minutes, it ends” [72]).For efforts on detecting irony from text see Reyes andRosso [72].

Using a simple scenario, we will illustrate how all theseproposed aspects of an opinion can appear and be anno-tated in text.

6 DISCUSSION AND FUTURE WORK

This paper focused on highlighting the differences betweenfive subjective terms and encouraging the NLP communityto treat them differently. During our research, we facedchallenges that could be further exploited as future work.

In compiling the definitions of the subjective terms, wenoted that affect, emotions, feelings, and sentiments havetheoretical underpinnings from evolutionary theory, psy-chology, folk psychology, and cognitive, neurological, phys-iological, and social constructivism (e.g., [53], [73], [74], [75],[76]). Given that all these theories may seem to contradictone another, a careful look shows that they just focus on dif-ferent aspects of the same concept. For example, evolution-ary theorists view affect, emotions, feelings, and sentimentsas being shaped by evolution to fulfill survival-benefitingfunctions [77] whereas social constructivists view them andtheir meaning as a product of culture and learned socialrules [75]. We presented a compilation of the definitions ofthe affective terms that are of interest from the computa-tional linguistics perspective. However, the convergence ofthe different psychological and cognitive theories uponwhich our definitions are based remains an interestingresearch venture.

Furthermore, for practical reasons, we restricted ourwork to the five subjective terms that are more frequentlyresearched in NLP, but we recognized that there are otherterms that also belong to this categorization, for example,attitude, mood, sensation, and temperament. As the fine-grained categorization of the terms increases, their distinc-tions also become fuzzier. Thus, as future work, using thedifferentiating factors uncovered in this work, we plan toinvestigate on a common framework for detecting othersubjective terms.

An aspect that we did not investigate in this paper iswhat analytic philosophy calls the use-mention distinction[78]. That is, there is a difference between an author using aword and mentioning the word. “Use of an expressioninvolves reference to what the expression refers to; mentionof an expression involves reference to the expression itself”[78]. Put simply, use is the application of the word meaning(e.g., I like chocolate), whereas mention is a statement about

Fig. 5. Schematic structure on an opinion.


the word per se (e.g., chocolate has two letters). This is a chal-lenge for NLP techniques applied to analyzing languageusage similar to detecting sarcasm, irony, exaggerations,and understatements. The use-mention distinction is impor-tant, for instance, when a researcher is interested in flaggingauthors who are abusive. The researcher might collect themention of the word “shit” as it is offensive, but the writermight mention it without using it to be offensive (see Wilson[79] on the use-mention distinction in NLP).

Research remains open to dive deeply into how the dif-ferent levels of analysis (word, phrase, sentence, paragraph,document, community, society, culture, etc.) might affectthe detection abilities of the subjective terms. The structureswe provided are to serve as a guide for researchers to judgeon the correct capture of the subjective terms.

7 CONCLUSION

This paper shed light on the differentiating factorsbetween subjective terms and identified their fundamen-tal concepts. We further gave suggestions on how theseconcepts could be incorporated to advance their detectionin natural language. The differentiating factors betweenaffect, emotions, feelings, sentiments, and opinionrevealed the following:

� Affect is non-conscious and is difficult to conceptual-ize in language, revealing that what can be detectedfrom text is the conscious expression of affect, whichwe found to be feelings and emotions.

� Feelings are conscious phenomena that have beenlabeled and they can be detected from text.

� Emotions are complex psychological phenomenathat are near impossible to detect in totality fromtext. What we were able to detect is the written con-scious experience of five factors (appraisals, feelings,physiological reactions, expressive behavior, andreadiness to act in a certain way), which constituteemotions. We also found that the use of any wordsto convey emotions is influenced by culture. We fur-ther recommend the inclusion of ethnographic stud-ies to answer questions such as “What role doesculture play in the linguistic expression ofemotions?” Answering that would enable NLPresearchers to create more robust ED detectionalgorithms.

� Sentiments are enduring emotional dispositions thathave developed over time about particular objects.Conclusions about sentiments in text have to be per-formed for a period. In turn, this will also help inimproving decision making.

� Opinions are personal interpretations of information,which may or may not be associated with an emotionor sentiment.

It is the recommendation of this paper that investiga-tions on affect, emotion, feeling, sentiment, and opinionin text should proceed with greater consideration intothe differences in terminologies and the role played bycultural, social, and personal differentiating factors toselect the proper type of analysis needed for the respec-tive tasks.

ACKNOWLEDGMENTS

This work was supported by the “Detecting and VisualizingEmotions and their Changes in Text” project (No. 14166),funded by the Academy of Finland.

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Myriam D. Munezero received the BS degreein computer science and mathematics fromthe University of Namibia, and the MS degreein computer science from the University ofJoensuu. She is currently working toward thePhD degree at the University of EasternFinland (UEF). She has worked for four yearsas a junior researcher at UEF in a projectfunded by the Academy of Finland. She is cur-rently a coordinator at UEF. Her researchinterests include the area of natural language

processing, particularly on detecting emotions from text. Herresearch in this area has resulted in four conference papers, oneco-authored conference paper and two journal papers.

Calkin Suero Montero received the engineeringmaster’s degree and computer science PhDdegree from Hokkaido University, Japan. She iscurrently a post-doctoral research fellow at theUniversity of Eastern Finland. She has expertisein human computer interaction and also hasextensive experience working within internationalenvironments in the fields of computational lin-guistic, sentiment analysis, novel interactiontechniques and usability and social acceptanceof technology. She has received two Best Paper

Awards from the IEEE Sapporo Section and her research has been pub-lished in world level international forums including MobileHCI andColing/ACL. She is a member of the IEEE, the IEEE Computer Societyand IEEE WIE Society.

Erkki Sutinen received the PhD degree in com-puter science, and the MSc degree in mathemat-ics from the University of Helsinki. He is currentlythe head of the education technology researchgroup at the University of Eastern Finland. Hisresearch interests include technologies for spe-cial education, contextualized IT education,visual and textual tools for learning, and naturallanguage processing methods for business intel-ligence and for emotion detection. He has pub-lished and supervised many students in the

above fields. He has received several research grants from the Acad-emy of Finland, The Finnish Funding Agency for Technology and Inno-vation (TEKES) and the European Union.

John Pajunen received the master’s degree inphilosophy in 2008. He is currently employed atthe University of Jyv€askyl€a as a universityteacher. His current research interests includeargumentation theory, logic, and philosophy ofscience. He is a member of IACAP.

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