WHEN ONLINE AFFECTS THE OFFLINE: THE EFFECT OF

MISINTERPRETATION IN ONLINE CHATS ON THE

EMOTIONAL WELL-BEING OF STUDENTS

Van den Bos, Lars, University of Utrecht, Princetonplein 5, Buys Ballot Gebouw, 3584 CC,

Utrecht, The Netherlands, larsvdbos@gmail.com

Van den Heuvel, Joey, University of Utrecht, Princetonplein 5, Buys Ballot Gebouw, 3584

CC, Utrecht, The Netherlands, joeyhilll@hotmail.com

Molenaar, Sabine, University of Utrecht, Princetonplein 5, Buys Ballot Gebouw, 3584 CC,

Utrecht, The Netherlands, s.molenaar95@gmail.com

Robeer, Marcel, University of Utrecht, Princetonplein 5, Buys Ballot Gebouw, 3584 CC,

Utrecht, The Netherlands, m.j.robeer@students.uu.nl

Abstract

Online chats have grown to become more popular over the past few years and, needless to say, the way

they distance themselves from time and place are great, but are there any negative consequences

connected to computer-mediated communication (CMC)? To be more specific, can misinterpretations

in CMC affect the emotional well-being of a person in some way? Previously done research indicated

that social skills and interpretations are important aspects in communication and should be taken into

account to uncover the answer to this question. Through the means of an online questionnaire,

information was gathered from 108 Information Sciences students. The analyses of the answers show

that there was a severe lack of females (only seven) in the sample and that other results did not prove

to be significant enough to accept the alternative hypotheses. Only negligible correlations between the

variables have been found (at most) and there were no significant differences present. The research

provides no evidence that misinterpretations in online chats affect the emotional well-being of an

individual.

Keywords: Computer-mediated communication (CMC), Emotional well-being, Misinterpretation,

Social skills, Gender, Students.

1 Introduction

Since the upswing of modern Internet facilities around the world, people have the ability to chat to each

other via a digital medium. The textual form of this chatter is commonly referred to as computer-

mediated communication (CMC) (Thurlow, Lengel & Tomic, 2004). The use of CMC has changed the

way people interact in various ways. Chatting to one another leads to large conversations that might be

interpreted elsewise, since there are no nonverbal cues involved in CMC (Walther, 1992).

Misinterpretation and misperception are terms that clarify the situation, but will not explain why this

occurs.

With this research project, the impact of misinterpretation in CMC on Information Science students has

been examined. The research was limited to this sample frame, since misinterpretation is different

between all kinds of populations and contexts (Jones, 1995). It is interesting to consider the effects on

relatively young people that use computers relatively often, which leads to interesting data on several

aspects, such as their social skills, emotional well-being and how adept someone is at interpreting a

particular chat in a particular context. The person should, for example, be able to determine the real

meaning of a particular conversation or be sure that the receiver of a joke also conceives this as such. A

better view on this aspect would lead to information that gives a more contextualized layer to CMC in

terms of testing fellow students. These students are ought to distinguish different and manage

information flows (Borko 1968), but they should also be capable of doing the same in CMC-information,

because they should not be negatively affected by an incorrect interpretation of a chat. Therefore,

scientific research has been conducted, literature was consulted, and psychological processes that are all

informative for the scientific process were explained, so that several interesting conclusions can be

drawn about this sample.

The research itself is interesting from a societal point of view, because CMC is an integral part of both

personal and professional communication (Ku, Chu & Tseng, 2012). Additionally, since there is still a

lot of knowledge to gather about this topic, the study is interesting from a scientific point of view. The

research project is based on a research question, and is being accompanied by several literature papers

that support the reasoning that will be conducted throughout the entire paper. This helped to

contextualize and clarify the gathered, unknown statistics of this sample.

The main objective of the research is to determine the effects of misinterpretation on online chatting.

The CMC will be studied using students in a one-on-one chat scenario. With this, the following research

question was formulated:

Is there misinterpretation among students in one-on-one instant computer-mediated communication that has a negative effect on the emotional well-being?

2 Theory

To form a theoretical foundation for the research, various papers that were relevant were studied. Even

though these papers have a lot to say about various aspects of CMC, misinterpretation and emotional

well-being, there are differences that make this research still viable to do. Emotional adjustments during

chatting have been analyzed by a few researches already, for instance by Zhe & Boucouvalas (2002),

where the researches tried to extract emotions from texts by computers. What is missing in this paper,

is that the focus really lies on the emotions in texts themselves, and not on how these are being

interpreted. This is exactly the gap that this research attempts to fill. The goal of the research, as

previously stated, is to see what the effects are when these emotions are being misunderstood in textual

communication, and what the causes are for these misinterpretations. As a matter of fact, no literature

could be found that is really similar to the topic that was researched.

There are, in fact, other papers that might be interesting for some aspects of this research, such as the

types of chat conversations. According to Link & Wagner (2006) three different types of CMC can be

defined: one-to-one, one-to-many and many-to-many. Moreover, reasons behind the use of emotions in

chats, and reasons behind using texting or chatting in general, instead of just talking are also aspects that

have been previously researched. Fullwood & Martino (2007) state that the use of emotions (through

the use of emoticons, for example) can help participants of a chat to be able to perceive the personality

and emotions of their chat partner(s). These are all very interesting papers, and they are useful for this

research, but they simply do not cover the principle of misinterpretation, which therefore is a unique

part of the subject to perform research on. The most relative papers might be Vandergriff (2013) and

Taesler & Janneck (2010), where the expression of emotion and use of emoticons and other typographic

markers used in chats are analyzed in these papers. Once again, there was no further elaboration of how

these are being interpreted by the one that is supposed to understand the receiving emotions from the

other contact.

In conclusion, the link between misinterpretation, CMC and emotions is a subject that has not been

researched (enough), which makes this research full of meaning.

3 Hypotheses

This research consists of three abstract constructs: emotional well-being, Communication Interpretation

Quota (CIQ), and social skills. The only variable in the current research is gender. The conceptual model

(Figure 1) gives a representation of the abstract constructs and the variable, and the relationships

between them. The relationships are represented by arrows, meaning that the construct or concept which

is pointing at another construct or concept has an effect on it. In the conceptual model, the dependent

variable, explained by the independent variable gender and the mediating variable CIQ, is emotional

well-being. The two independent variables, namely social skills and gender, explain a students CIQ and emotional well-being respectively. The CIQ is explained by social skills and it explains emotional well-

being. Thus, this is a mediating variable. In the following subsections, the conceptual model and its used

terms are elaborated.

Figure 1. Conceptual Model

3.1 Emotional well-being

First of all, emotional well-being is the main abstract construct in the conceptual model. It is the

construct that is affected by other parts in the conceptual model but does not affect other constructs or

variables by itself. Eventually, this construct is where the key focus in the research lies, and is therefore

seen as the main construct in this research.

Emotional well-being can be described in various ways. It can relate to the quality of someone's life,

having aspects like personal well-being, self-esteem, productivity and happiness. A good emotional

well-being will also reduce chances of stress, disorder and sleeping problems (Fredrickson & Joiner,

2002). This concept - since it is an abstract construct - is key in the research for a potential effect of

misinterpretation in chats on the emotional well-being. This is why all the arrows end up in this abstract

construct in the conceptual model, assuming that gender and the Communication Interpretation Quota

directly affect the emotional well-being.

To determine a students emotional well-being in the sample, a previously created scale by the World Health Organization: Regional Office for Europe (1998) was used. This scale consists of five statements

which are used to measure the participants emotional well-being on a scale of 1-100. The questions in this scale were implemented within the survey as a key part to gaining insight in the emotional well-

being of the student.

3.2 Communication Interpretation Quota (CIQ)

To be able to measure the amount of misinterpretations, a self-constructed abstract construct was added,

the Communication Interpretation Quota, or CIQ for short. CIQ determines the frequency of

misinterpretation in small chat conversations that have been created for the research. If there is no case

of misinterpretation, the participants CIQ will increase by one point. The CIQ is then transformed to a scale ranging from zero to one, with one being no misinterpretation at all, and zero meaning that all the

chats were misinterpreted. The right interpretation of a chat is determined by giving four multiple choice

answers, of which only one corresponds with an answer that the sender would (a) find appropriate to not

notice that there has been a case of misinterpretation, or (b) think that there has not been a

misinterpretation at all.

The Conflict Research Consortium (n.d.) suggests that ambiguous messages are likely to be

misinterpreted. People tend to clarify these messages by using their own expectations. This

misinterpretation can lead to social conflict, which in itself can lead to negative affect (Abbey, Abramis

& Caplan, 1985). Negative affectivity involves the experience of negative emotions and poor self-

concept (Watson & Clark, 1984). Even though not all the aspects of this relationships have been

researched, it shows that there is a possible negative effect of misinterpretation of messages on how

people perceive their own emotions. It is expected that students who had more cases of misinterpretation

in the CIQ questions, and therefore a lower CIQ, will have a significantly lower emotional well-being

after answering the CIQ questions than before answering them. This leads to the following hypothesis:

H1: A lower CIQ negatively affects the emotional well-being.

3.3 Gender

The variable that affects the emotional well-being is gender. This is a variable that is based on the

characteristics of an individual, and can be measured precisely. Logically, the variable gender can only

have two possible values: male or female. Previous research by Simon (2014) states that females are

usually more negative about their own well-being than men. Men report more frequent positive, and less

frequent negative feelings than women. Men and women may react differently to misinterpretation and

that is why this aspect needs to be taken into account in this research. This leads to the second hypothesis:

H2: Men tend to have a higher overall emotional well-being in comparison to females.

3.4 Social Skills

The last abstract construct is social skills. The social skills of an individual is the ability to communicate

with other human beings, both verbally and non-verbally, and understanding them (SkillsYouNeed,

n.d.). In short, whether an individual is, or is not, sociable. In the conceptual model, it was expected that

social skills affect the CIQ.

A vital part of understanding others, and responding to them, is based on the ability of individuals to

effectively recognize and use nonverbal behavior (Feldman & Rim, 1991). Having developed social

skills will make people able to understand their conversation partner better. Being sensitive to the

thoughts and feelings of others is key to successfully establish and maintain social relationships (Pickett,

Gardner & Knowles, 2004). Socially skilled people will be better in interpreting conversations correctly,

have a better sense for what direction the chat is going in, and are more skilled in forming appropriate

reactions to the conversation partner. Therefore, social skills affect the chances of misinterpreting

conversations and, in doing so, affect the CIQ. This induces the third, and final, hypothesis:

H3: There is a positive correlation between social skills and CIQ.

4 Method

4.1 Participants

The questionnaire was filled in by 108 students following the course Scientific Research Methods at the University of Utrecht. In general, students form a suitable and adequate sample for this research.

They are not just required to use the computer quite regularly for study-related activities, but a fair

amount of young Dutch people also suffer from negative emotions, such as anxiety and depression

(CBS, 2014). The only downside that could be foreseen was the low quantity of female students

following the course, which also reflected in the actual number of females filling in the questionnaire

(N = 7).

4.2 Materials

A questionnaire is a suitable method to answer the research question. Currently, there are some scales

that already exist, which could be used to determine ones mental condition or state. This was expanded with short made-up chats, with some context added to them. Subsequently, the correct interpretation of

said chat (the feelings of both chatters involved, the meaning of the conversations and the purpose of

the conversation) was determined. This was used to see if the students in the sample were able to

interpret the chats correctly, or in other words, if there was a case of misinterpretation. Furthermore, the

questionnaire was an easy way to reach a lot of students, while making sure they got the exact same

questions. As a consequence, the differences in the answers were dependent on the individual itself, and

not due to the way the questions were asked.

The questions that were devised for the questionnaire have been categorized, and the answers to these

questions were related to a specific part of the research (the entire questionnaire can be found in the

Appendix A). All questions belong to a variable or abstract construct present in the conceptual model.

Putting aside the general questions, the first question that truly mattered to the research was question

two, determining the gender. Questions three through seven and 21 through 25 have been used to

ascertain the emotional well-being of the participants in the sample. Subsequently, questions eight

through 12 gave insight in a participants social skills, and to conclude, the remaining questions (questions 13 through 20) determined the CIQ of a participant. There was a grand total of 25 questions.

Since the hypotheses were based on the conceptual model, the answers to the questions in the

questionnaire provided enough information for conclusions and determination of whether the alternative

hypotheses should be accepted or rejected. A further elaboration on the questions can be found below.

The questions will be described in order of appearance.

First of all, to measure the variable gender, a binary scale question was asked; simply What is your sex?. The percentages of these amounts were calculated by dividing the amount of males by the sample size, the same was done for females.

Secondly, a participants social skills were measured by asking them to determine how well five statements about their social skills fitted to themselves. The social skills scale had to be accurately

measuring social skills and it should consist of fewer than seven questions. Since none of the social

skills scales could be found that met these requirements, a self-constructed scale was added. This scale

consists of one Likert scale for each of five statements that are closely related to social skills. Hall (1979)

divided social skills into two broad classes of sending and receiving. Riggio (1986) expands this by

subdividing social skills into basic dimensions, which involve skill in sending, receiving and controlling

information. Since the participants answering the questionnaire were taking the role of the receiver, the

five statements also focused on assessing the receiver class of social skills. Furthermore, the National

Research Council (2010) states that social skills means having skills in interpreting verbal and nonverbal

information to respond appropriately. According to the National Research Council, social skills are

equal to complex communication. By adding this information to the scale, the statements were used to

determine someones social skill by rating the awareness of reasons behind communication, awareness of peoples means and intentions through chat, phone and real life conversations. In other words, if the participants viewed themselves as being successful in the receiver role of both verbal and nonverbal

complex communication. The scores were then added up, creating one total score for each individual.

The total score was used for the hypotheses testing. This scale, consisting of five items, was found to be

reliable ( = .839).

Thirdly, to measure the abstract construct emotional well-being, five seven-point Likert scales were used

for the statements that relate to emotional well-being. Questions that measure the emotional well-being

were filled in before and after the test with the chat examples in the questionnaire. The scores of the

individuals were then applied to a previously created scale devised by the World Health Organization:

Regional Office for Europe (1998). This is a scale that could measure someones emotional well-being with a limited amount of statements. The scores of the five questions were then added up, and

transformed into values ranging from zero to 100, as was also done by the World Health Organization.

The emotional well-being of a participant was determined twice in the questionnaire. This was done to

appropriately form an answer to the first hypothesis. To properly answer the first hypothesis, not the

effect of the CIQ on the overall emotional well-being is interesting, but whether the emotional well-

being was negatively affected after there were potential cases of misinterpretation. For hypothesis one,

it was expected that more misinterpretations correlate with a bigger negative influence on emotional

well-being, and thus with a bigger negative difference between the emotional well-being after the

questions concerning misinterpretation and the questions before that. Both of the times that the scale

was used in the questionnaire, it was found that the five items forming the scale were internally consist

according to Cronbachs alpha, with alpha scores of .771 and .761 respectively.

Finally, the CIQ score was measured over eight multiple choice questions with one correct answer each,

meaning that the other multiple choice answers were false. The participants were informed of the chat

environment for every single chat, by adding a general context of the chat followed by a part of the

conversation up to the point the participant had to form an answer. In the context, information such as

the nature of the chat, a comprehensive description of the conversation partner, and the time of day the

chat takes place were given to the participant. By providing this context and the chat itself, the participant

should be sufficiently informed to choose the correct reply to the chat, in order to avoid

misinterpretation.

After gathering data from the questionnaire, the CIQ score was calculated by undertaking multiple steps.

Firstly, the given answers per question were compared to the correct answer as determined beforehand.

The correct answers to the CIQ questions are marked by the bold-type text in the questions themselves

(13 20) in Appendix A. Correct answers were given one point, incorrect answers were given zero points. Secondly, the total of the score of an individual was calculated. Finally, this was then divided by

eight (due to the presence of eight chat examples). This resulted in scores varying from zero to one. The

scale was eventually used to test hypotheses about where one of the two variables was the CIQ score.

No internal consistency reliability, tested by Cronbachs alpha, was calculated for the CIQ questions, because it is only an indicator if the both chat partners are interpreting the chat in the same way. As

aforementioned, the CIQ is merely an indicator for the frequency of misinterpretations by a student in

the eight chats combined. None of these eight questions are meant to be interrelated, and therefore no

internal correlations were expected to be present.

4.3 Procedure

The questionnaire started by generally informing the students about the research and the questionnaire,

itself. This was done in form of a general story about and behind this research and the questionnaire. On

purpose, the word misinterpretation in the title was changed into interpretation. This was done to ensure that participants would fill in the CIQ questions in the questionnaire according to their own

thought, instead of actively searching for an obscure answer. The actual content started off with a general

theoretical basis about misperception and misinterpretation in computer-mediated communication, to

give the participants an idea of what the questionnaire is about. Secondly, the participants were shown

gave a short introduction about the abstract construct emotional well-being, and related that to the

research. The participants were then shown the research question for some extra information. Thirdly,

the participants were given a short overview of how the components of the questionnaire were ordered

and what kind of questions could be expected. Finally, the introduction ended by giving a time indication

to fill in the questionnaire (five to ten minutes) and thanking the participants in advance. The actual

introduction given to the students can be found in Appendix A.

The participants who filled in the questionnaire were not treated any differently across certain

conditions. Male or female, and which team the participant was from, did not make any difference in

the way participants had to fill in the questionnaire.

After finishing the questionnaire, the participants were thanked for filling in the survey, thereby

informing the participants the questionnaire was done.

5 Results

Data from one participant were dropped because the data was found to be corrupt.

The first hypothesis, A higher recognition of CIQs in chats leads to a higher emotional well-being, was tested using a Pearsons correlation test. For the test, the Communication Interpretation Quota of students (M = .36, SD = .14) were compared to the difference in their score of emotional well-being

before and after the CIQ questions (M = -1.14, SD = 9.60). Analysis showed an insignificant and

negligible negative correlation, r(107) = -.12, p = .103, one-tailed.

Hypothesis two, which states that men tend to have a higher overall emotional well-being in comparison

to females, was tested using the independent sample T-test. In this case, the differences between gender

in their emotional well-being, both before and after, were tested. The low number of female students (N

= 7), compared to the number of male students (N = 101) that filled in the study, means that no

conclusions based on gender can be drawn from this data. Analysis showed no significant difference

between males (M = .58, SD = .14) and females (M = .60, SD = .11) on the emotional well-being

measured before the CIQ-test, t(106) = -.31, p = .381, one-tailed. Additionally, analysis also did not

show a significant difference between males (M = .57, SD = .14) and females (M = .56, SD = .11) in

their emotional well-being (after), t(106) = .22, p = .413, one-tailed.

Figure 2. Scatter plot for the correlation of a students Communication Interpretation Quota and their social skills

For the third hypothesis, the correlation between a students social skills and their CIQ was measured using Pearsons correlation. As can be seen in Figure 2, the spread of the dots on the scatter plot provide no clear linear trend between the two variables. Even though there seems to be a positive association

with constant scatter, this relationship is too weak to show any clear relationship. The coefficient of

determination (R2) confirms this, with only 1.6% common variance between the two variables. The lack

of a correlation as suggested in the scatter plot is also shown in Pearsons correlation test, where no significant correlation was found between social skills (M = 28.22, SD = 4.16) and Communication

Interpretation Quota (M = .36, SD = .14), r(107) = .13, p = .098, one-tailed.

6 Conclusion

In an effort to find a negative effect of misinterpretation on the emotional well-being of students in one-

on-one computer mediated communications, data gathered from a self-constructed questionnaire, filled

in by 108 students following the course Scientific Research Methods, were collected. A few conclusions

can be drawn in relation to the alternative hypotheses, based on the gathered data. Results from the

questionnaire regarding the first alternative hypothesis, H1 A lower CIQ negatively affects the emotional well-being, produced no statistically significant correlation. Abbey, Ambramis & Caplan (1985) implied that misinterpretation could lead to negative affect. This negative affect involves

negative emotion and poor self-concept (Watson & Clark, 1984). Hence, a significant negative

correlation was expected between the CIQ and the difference in emotional well-being. Even though the

correlation was not significant, it demonstrated a negative correlation.

The questionnaire displayed no evidence that the second alternative hypothesis, H2 Men tend to have a higher overall emotional well-being in comparison to females, is true. Results were inconclusive, due

to the lack of females in the sample. Therefore, this null hypothesis cannot be disproven and the

alternative hypothesis that has been devised should not be accepted. This conclusion is not in line with

previous research, because Simon (2014) suggested that men are generally more positive about their

own emotional well-being than women.

Likewise, the results revealed no indication that higher social skills lead to a higher CIQ. Consequently,

the last alternative hypothesis, There is a positive correlation between social skills and CIQ, should also be rejected. The only evidence that was found regarding this aspect of the questionnaire is that there

might be an extremely weak positive correlation between social skills and CIQ, which should be

neglected altogether. The absence of a significant correlation is in disagreement with Pickett, Gardner

and Knowles (2004). They see being sensitive to thoughts and feelings as key to social skills.

To conclude, misinterpretation among students in one-on-one computer-mediated communication does

not have a negative effect on the emotional well-being of said students. According to the theory

described earlier, online chats can have a certain emotional weight to them and can be interpreted

incorrectly. Apparently though, no evidence has been found in this research to prove that this

misinterpretation does in fact negatively affect the emotional well-being.

7 Discussion

There are several limitations to this research that have a potential effect on either the quality of the

findings, or the ability to effectively answer the hypotheses. Firstly, there was a lack of show-up females

in the sample. The sample size contained 108 participants, of which only 6.48% were women. Even

though the difference between genders may be present in the general population, the difference between

the two genders in this sample had to be very large to be statistically significant.

Additionally, this gender problem is part of the second limitation in the research. The sample that filled

in the questionnaire is difficult to generalize. This difficulty has two main reasons. First and foremost,

because the actual percentage of females in universities in the Netherlands is 52% (CBS, 2012),

compared to the 6.48% females in the sample. Secondly, because it is questionable if Information

Sciences students are a homogeneous representation of the overall student population.

The third limitation of the research became evident in the two self-constructed abstract constructs.

Although the first of these two, social skills, exhibited a high internal consistency reliability, the

statements making up social skills rest on a frequency of time. This frequency of time was distributed

over seven possible Likert scale answers, ranging from none of the time to all of time, that could be interpreted differently by each individual. This different interpretation of frequencies could mean that

the answers on this Likert scale are incomparable. Two participants intending to give the same frequency

of time could choose two different Likert scale answers, and likewise, two participants choosing the

same answer could have a different frequency of time in mind.

Besides social skills, there were several problems encountered with the Communication Interpretation

Quota, the second self-constructed abstract construct. Firstly, students were not given an indicator

whether the chosen answer lead to misinterpretation or not, which could explain the lack of a significant

effect on the emotional well-being. As was apparent in the theory, the emotional well-being of a person

is only affected if there is a known misinterpretation between both conversation partners. Not giving an

indication of the occurrence of this misinterpretation made a theoretical effect on a persons emotions improbable. Secondly, since the answers to the CIQ questions were limited to multiple choice, students

could not form their own reaction to the chat, as is done in a real conversation. This imposes a potential

misinterpretation of the four given answers students could choose from. Even though one of the four

answers is the correct answer that is expected by the sender, and is therefore the answer that is correct

to avoid misinterpretation, it does not mean that the receiver could not have formed an answer that would

keep up the conversation, without the sender even knowing that his sent message was misinterpreted.

For instance, chats could change topics, or reactions themselves could be ambiguous. This shows that

for the creation of a new abstract construct, a whole process is needed to ensure that it is both reliable

and valid in all possible ways. For example, it is currently unknown if the CIQ gives a good indication

of misinterpretation. Unfortunately, since the main focus of the research was on providing an answer to

the main question, there was no room for forming good and solid abstract constructs.

Finally, the method chosen to gather data for the hypothesis, a questionnaire, posed four main problems

itself. Firstly, by establishing an individuals emotional well-being within just one survey, the timespan between the two measurements was really short. Chat sessions themselves could even outlast the length

of the survey. Even though a students emotional well-being might be negatively affected by misinterpretation, no indications were found for when this would occur. This might be directly after the

chat, or there might be a delay before this takes place. Secondly, the usage of Likert scales in the

questionnaire introduced a central tendency bias. Students filling in the questionnaire tend to avoid the

most extreme answers, such as I feel no commitment at all in the emotional well-being questions, because the occurrence of these is very scarce in the minds perception. Thirdly, in a survey people have to review themselves, which adds a social desirability bias. There is a possibility that students will put

themselves in the best possible light, instead of giving an objective answer. Lastly, the multiple choice

questions to measure ones CIQ are subject to the probability of guessing a correct answer.

Future research should ensure that the two newly introduced abstract constructs are highly reliable and

valid. Especially, it should form a good abstract construct for measuring misinterpretation in chats.

Furthermore, future research should focus on experimental research to minimize potential effects of

bias, control extraneous variables, and compensate the shortcomings the questionnaire brings along.

References

Abbey, A., Abramis, D. J., & Caplan, R. D. (1985). Effects of Different Sources of Social Support and

Social Conflict on Emotional Well-Being. Basic & Applied Social Psychology, 6(2), 111-129.

Borko, H. (1968). Information science: What is it? American Documentation, 19(1), 3-5.

CBS. (2012). Jaarboek onderwijs in cijfers. The Hague: CBS.

CBS. (2014). Gezondheid, aandoeningen, beperkingen; leeftijd en geslacht. Retrieved from

http://statline.cbs.nl/StatWeb/publication/?VW=T&DM=SLNL&PA=81174NED&D1=47-52,60-

65&D2=1-2&D3=1-4&D4=0&D5=l&HD=111101-1022&HDR=G4,G3,G1,G2&STB=T.

Conflict Research Consortium. (n.d.). Misinterpretation of Communication. Online Training Program

on Intractable Conflict (OTPIC) Retrieved September, 25, 2014, from

http://www.colorado.edu/conflict/peace/problem/misinter.htm

Feldman, R. S., & Rim, B. (1991). Fundamentals of Nonverbal Behavior: Cambridge University

Press.

Fredrickson, B. L., & Joiner, T. (2002). Positive emotions trigger upward spirals toward emotional

well-being. Psychological Science, 13(2), 172-175.

Fullwood, C., & Martino, I. M. (2007). Emoticons and Impression Formation. Applied semiotics: a

learned journal of literary research on the World Wide Web, 7(19).

Hall, J. A. (1979). Gender, gender roles, and nonverbal communication skills. In R. Rosenthal (Ed.),

Skill in nonverbal communication (pp. 32-67). Cambridge, MA: Oelgeschlager, Gunn and Hein.

Jones, S. G. (1994). CyberSociety: Computer-Mediated Communication and Community (4th ed.):

SAGE Publications.

Ku, Y.-C., Chu, T.-H., & Tseng, C.-H. (2013). Gratifications for using CMC technologies: A

comparison among SNS, IM, and e-mail. Computers in Human Behavior, 29(1), 226-234.

Lisa, L., & Daniela, W. (2009). Computer-Mediated Communication in Virtual Learning

Communities. In A. Chee Siang & Z. Panayiotis (Eds.), Human Computer Interaction: Concepts,

Methodologies, Tools, and Applications (pp. 316-322). Hershey, PA, USA: IGI Global.

National Research Council. (2010). Exploring the Intersection of Science Education and 21st Century

Skills: A Workshop Summary. Washington DC: National Academies Press.

Pickett, C. L., Gardner, W. L., & Knowles, M. (2004). Getting a cue: The need to belong and

enhanced sensitivity to social cues. Personality and Social Psychology Bulletin, 30(9), 1095-1107.

Riggio, R. E. (1986). Assessment of Basic Social Skills. Journal of Personality of Social Psychology,

51(3), 649-660.

Simon, R. W. (2014). Sociological Scholarship on Gender Differences in Emotion and Emotional

Well-Being in the United States: A Snapshot of the Field. Emotion Review, 6(3), 196-201.

SkillsYouNeed. (n.d.). What are Social Skills? Retrieved September 25, 2014, from

http://www.skillsyouneed.com/ips/social-skills.html

Taesler, P., & Janneck, M. (2010). Emoticons and impression formation: the impact of emoticon use

on the perception of online communication partners. Gruppendynamik Und

Organisationsberatung, 41(4), 375-384.

Thurlow, C., Lengel, L., & Tomic, A. (2004). Computer Mediated Communication: SAGE

Publications.

Vandergriff, I. (2013). Emotive communication online: A contextual analysis of computer-mediated

communication (CMC) cues. Journal of Pragmatics, 51(0), 1-12.

Walther, J. B. (1992). Interpersonal Effects in Computer-Mediated Interaction: A Relational

Perspective. Communication Research, 19(1), 52-90.

Watson, D., & Clark, L. A. (1984). Negative affectivity: The disposition to experience negative

aversive emotional states. Psychological Bulletin, 96(3), 465-490.

World Health Organization: Regional Office for Europe. (1998). Wellbeing measures in primary

health care: The DepCare Project. Paper presented at the Consensus meeting, Stockholm, Sweden.

Zhe, X., & Boucouvalas, A. C. (2002). Text-to-emotion engine for real time internet communication.

Proceedings of International Symposium on Communication Systems, Networks and DSPs, 164-

168.