Flaming among ®rst-time group support system users
Milam Aiken
a,*, Bennie Waller
b,1aSchool of Business Administration, University of Mississippi, University, MS 38677, USA bSchool of Business, Francis Marion University, P.O. Box 100547, Florence, SC 29501-0547, USA
Received 24 March 1999; accepted 1 August 1999
Abstract
Numerous bene®ts, including increases in ef®ciency, effectiveness, and participant satisfaction, have been noted in the literature when electronic meetings are used in place of traditional, oral meetings. However, several costs, or process losses, have also been observed, including an increase in `¯aming' characterized by insults or even obscenities. This paper describes how ¯aming may be correlated with numerous task and group member characteristics. Results of a case study show that a large number of ¯ames are unrelated to the topic and that a small minority of those writing comments are responsible for the majority of ¯ames. No variables were found to be signi®cant predictors, but its incidence was exclusively among males.
#2000 Elsevier Science B.V. All rights reserved.
Keywords:Electronic meetings; Group support systems; Brainstorming; Disinhibition; Flaming
1. Introduction
Managers spend a large percentage of their time in meetings, but traditional, oral meetings are often inef®cient and ineffective. According to a study at the University of Southern California in Los Angeles, the average meeting has no written agenda, and the purpose of the meeting is accomplished only 50% of the time [13]. Further, 25% of the participants feel they waste time on irrelevant issues, 33% of the participants feel pressured to advocate opinions publicly though they privately disagree with them, and 33% of the participants feel they have minimal in¯uence on the meeting.
Group support systems (GSSs) were developed to improve meetings. Using this technology, group mem-bers are able to participate more and state their opinions anonymously while all of the discussion may be recorded automatically on a computer disk for printout and possible distribution after the meeting [5].
There are some disadvantages of using the technol-ogy, however. In most electronic meetings, partici-pants share comments anonymously or with a pen name. While this promotes more candid comments, it also may increase ¯aming, i.e. comments intended to offend others [15]. While somewhat subjective, at the extreme ¯aming includes obscenities and other inap-propriate comments, and may lead to avoidance of the technology [16].
While some researchers have proposed possible causes of ¯aming in the GSS environment and a few studies have looked at the incidence of ¯aming *Corresponding author. Tel.:1-662-915-5777.
E-mail address: aiken@bus.olemiss.edu (M. Aiken). 1Tel.:1-843-661-1501.
on a group basis, none that we have found have tracked ¯aming on an individual basis, possibly due to limita-tions of the software. The purpose of this effort was to examine several user characteristics as they relate to the number of relevant, irrelevant, and ¯aming com-ments generated by each participant.
2. Background
There appears to be little consensus on an exact de®nition of ¯aming [10]. Obscenities and insults are easily recognized as instances of it, but a large degree of subjectivity is needed to distinguish impassioned criticism from insult. At one extreme, a study included any comments with exclamation points as instances of ¯aming [19], but most researchers de®ne ¯aming as hostile comments directed at a person rather than an idea.
Experience with over 1000 participants in 70 meet-ings has shown that ®rst-time users become disinhib-ited through the use of an anonymity feature in the software, and there is frequently laughter about jokes that all participants view at the same time [6]. Many ®rst-time GSS participants have never been able to express their ideas with complete anonymity while simultaneously viewing others' comments and wish to try out the feature with wild, if not socially-unaccep-table views. Continued use of such systems may reduce the incidence of this type of ¯aming, however, as the novelty wears off.
Several studies have found more ¯aming in anon-ymous electronic meetings than in traditional meet-ings. For example, one study using students who did not know each other for hypothetical tasks found a large amount of ¯aming when social control breaks down [11]. Other studies, however, have found little or no increases in ¯aming [14,18]. For example, one used managers and professionals who were about 43 years old and employed in a conservative corporation; they found little disinhibited behavior. This may be because the members were part of a social organization having ongoing expectations of common group identity and shared activities to accomplish [9]. Similarly, a study of mature bank employees generating a strategic plan using a GSS found no incidences of ¯aming [1].
Social norms and culture may play a large role. For example, groups from Asia are often more restrained
and consensus-seeking and rarely generate in¯amma-tory comments, even in anonymous electronic meet-ings [3,4]. In addition, the incidence of ¯aming and irrelevant comments may be reduced signi®cantly by strong admonitions from the group facilitator to refrain from such conduct [17]. Although a few the-ories have been proposed, no studies have found signi®cant predictors of why ¯aming comments are made by speci®c individuals.
3. Case study
To examine why ¯aming occurs in an anonymous, electronic meeting, a case study was conducted.
3.1. Subjects
Two groups of 45 undergraduate Business students discussed two topics using a GSS as part of a required assignment in their electronic classroom at their reg-ularly scheduled meeting time. The groups were fairly homogeneous in age, education, typing speed, and computer experience. Approximately 40% of each group were female.
3.2. Task
After a brief explanation of how to use the software, the subjects spent 10 minutes generating comments on two topics:
1. `Should the President of the United States be removed from of®ce? Why or why not?'
2. `How can we solve the parking problem on the campus?'
Topic 1 was chosen because of the level of con-troversy surrounding the issue at the time of the assignment, the subjects were likely to have knowl-edge of it, and we felt a controversial topic could result in more ¯aming. Topic 2 was chosen because it was believed to be less controversial, and it has been used in prior experiments, e.g. [8].
3.3. Procedure
Following each idea generation task, participants completed an online questionnaire using a seven-point Likert scale with 1 equivalent to not controversial, no knowledge, etc. and 7 equivalent to extremely con-troversial and a great deal of knowledge:
1. How controversial is this topic?
2. How much do you know about this topic? 3. How familiar are you with electronic
communica-tion?
4. How important is this topic?
5. How satisfied are you with the meeting process?
In addition, we recorded the sex of each individual and the number of the computer that the participant was using.
3.4. Dependent variable measures
The number of relevant, irrelevant, and ¯aming comments were measured through a content coding of transcripts for each participant. The electronic meeting software automatically recorded comments from each group member in separate ®les and used the same identi®er (the computer number) for each mem-ber's questionnaire answers. Coding was conducted by two independent observers.
Relevant comments were deemed to be those ideas related to the topic and not in¯ammatory (e.g., `Build a parking garage'). Flaming comments were judged to be those which might offend somebody in the group. These comments included those which insulted another person in the group by name (e.g., `Teach_how to drive'), obscenities, and sexual refer-ences. Many of these ¯ames were also irrelevant, but were not counted as such. Irrelevant comments were counted as those not related to the topic and not in¯ammatory (e.g., `When can we get out of here?'). Two independent coders evaluated transcripts of the meetings and agreed on 98% of their selections, indicating adequate inter-rater reliability.
4. Results
4.1. Independent variables
The results of the questionnaires and the number of comments generated for both groups are shown in
Table 1. As we suspected in designing the tasks, subjects believed that the removal of the president was more controversial (F4.69, p0.032). Park-ing was believed to be more important, but not sig-ni®cantly so (F1.25, p0.265). The subjects' knowledge of both problems was approximately the same (F0.17,p0.68), and their satisfaction with the meeting process discussing each topic was not signi®cantly different (F1.02, p0.314). The question regarding their electronic communication experience was repeated in the questionnaires. Although, the mean was slightly different, it was not signi®cant (F0.45,p0.504). The results of the questionnaires and the number of comments gen-erated for group 1 and group 2 are shown in Tables 2 and 3.
4.2. Comment analysis
Table 4 shows the number of relevant, irrelevant, and ¯aming comments for each group by topic. A Table 1
Questionnaire results (overall)
Parking President
Mean SD Mean SD
Controversy 4.52 1.86 5.19 1.82
Knowledge 4.32 1.82 4.20 1.63
Communication 3.23 1.73 3.44 1.97
Importance 4.93 1.78 4.56 2.13
Satisfaction 4.19 1.93 3.87 1.88
Relevant 1.48 1.59 0.73 0.84
Irrelevant 0.33 0.56 0.41 1.13
Flames 0.48 0.88 0.77 1.44
Table 2
Questionnaire results (group 1)
Parking President
Mean SD Mean SD
Controversy 4.26 1.87 5.38 1.78
Knowledge 3.66 1.41 4.54 1.56
Communication 3.49 1.77 3.95 1.72
Importance 5.11 1.66 4.84 2.05
Satisfaction 4.14 1.59 4.51 1.77
Relevant 1.83 1.72 0.68 1.00
Irrelevant 0.31 0.47 0.62 1.48
large amount of `free-riding' was exhibited by the subjects. Although they were encouraged to write comments, only 25 of the 45 in the ®rst group wrote about the parking problem and only 20 wrote about the president. In the second group, only 22 of 45 wrote about the president and only 21 about parking. A large portion of the groups wanted to just read others' comments.
Flaming comments were written by a small minor-ity of the participants. In the ®rst group, ¯ames were written by ®ve participants (20% of the total who wrote comments) when discussing parking and 10 participants (50% of the total who wrote comments) when discussing the second problem. All ®ve of those who wrote ¯aming comments for parking also wrote ¯aming comments about the second issue. In the second group, ¯ames were written by four participants (19% of the total who wrote comments) when dis-cussing parking and 10 participants (27% of the total who wrote comments) when discussing the president. Two of the four who wrote ¯aming comments for the ®rst topic also wrote ¯aming comments for the second topic. Of those who wrote ¯aming comments, one or
two wrote a disproportionate share. For example, one participant in group 1 discussing the president wrote seven ¯ames, three irrelevant comments, and no rele-vant comments. That is, one of 10 who wrote ¯ames wrote 22% of the total. Finally, all of the participants who wrote ¯ames were male. A similar result was found in a study of Japanese GSS participants in which females were more polite and readers of their anon-ymous comments could often distinguish those written by them [2].
Most of the ¯ames were not relevant to the topic (60%), and many were insults to a particular person in the group directly by name (30%) or indirectly (14%), e.g. `The person who wrote comment number 45 is a_'. There was no statistically signi®cant difference between the number of irrelevant ¯ames based upon which topic was chosen. Some of the ¯ames were repeated, and many referred to or built upon other ¯ames.
The topic order may have had an effect on the number of comments generated and the amount of ¯aming. The number of ¯aming and irrelevant com-ments increased when the ®rst group switched from the parking problem to the president, while the num-ber of relevant comments decreased. The numnum-ber of ¯ames and irrelevant comments increased when the second group switched from the president to the parking problem, but the number of relevant com-ments also increased. The subjects may have learned how to use the software more and its capabilities. In addition, ¯aming might have spawned more ¯aming in response.
The number of relevant comments about parking was signi®cantly greater than the number about the president (F12.65,p0.001) but the numbers of irrelevant and ¯aming comments were not signi®-cantly different (F0.28, p0.599) and (F2.15,p0.145), respectively.
4.3. Variable correlations
A Pearson correlation analysis was conducted on the data, and signi®cant results (at a.05) were found among several variables. Subjects with more knowledge about the topics perceived them as more controversial (R20.395, p0.0001) and more important (R20.309, p0.0002), had more elec-tronic communication experience (R20.205, Table 3
Questionnaire results (group 2)
President Parking
Mean SD Mean SD
Controversy 5.00 1.86 4.79 1.84
Knowledge 3.87 1.65 5.00 1.95
Communication 2.95 2.10 2.97 1.68
Importance 4.29 2.20 4.74 1.90
Satisfaction 3.24 1.79 4.24 2.26
Relevant 0.79 0.66 1.12 1.37
Irrelevant 0.21 0.58 0.35 0.69
Flames 0.42 0.89 0.62 0.99
Table 4
Comment analysis
Relevant Irrelevant Flaming
Group 1
Parking 54 6 6
President 19 21 32
Group 2
President 23 5 6
p0.0139), were more satis®ed with the meeting process (R20.244,p0.0032), and generated more relevant comments (R20.186, p0.0255). Those with more electronic communication experience also believed the topics were more important (R20.204,
p0.014), were more satis®ed with the meeting process (R20.173, p0.0377), generated more relevant comments (R20.266, p0.0064), and generated more irrelevant comments (R20.164,
p0.0492). The perceived level of importance was also signi®cantly correlated with the perceived level of controversy (R20.369,p0.0001). The topic was signi®cantly correlated with the level of controversy (R20.179, p0.032) and the number of relevant comments (R2 ÿ0.286,p0.001). Several of these results are due to cross-correlation, however.
None of the variables were found to be signi®cant predictors of ¯aming, although satisfaction with the meeting process (F2.12, p0.055) and impor-tance of the topic (F2.13,p0.054) were close to our threshold levela0.05. There were two
post-factopredictors of ¯aming, however: the number of
relevant comments (F3.84,p0.001;R20.062) and the number of irrelevant comments (F7.79,
p0.001;R20.356,p0.001).
5. Discussion
Kitchens [12] proposed that ¯aming is a function of gender, age, race, alcohol consumption, locus of con-trol, importance of the topic, satisfaction with the meeting, anonymity, purpose of the ¯ame, presence of formal rules, and authority. We did not test all of these, but found that gender plays an important role: all of the ¯ames were generated by males. We found no signi®cant correlation between ¯aming and satis-faction with the meeting, however. Anecdotal evi-dence from conducting numerous GSS meetings also suggests that strong admonitions from the group leader or facilitator often suppresses the incidence of ¯aming. In addition, group members must also be encouraged to write ideas to overcome free riding [7]. Thus, the group facilitator's leadership has a strong role to play.
Most of the ¯ames were not related to the topic, suggesting that the topic may not matter. Rather, ¯ames are probably due to the characteristics (such
as gender, level of maturity, hostility, etc.) of the individual writing them. Only a small minority of those writing comments generated ¯ames.
Although there were several interesting correlations among the variables (e.g., those with more knowledge about the topic and those with more electronic com-munication experience were more satis®ed with the meeting), we found no signi®cant predictors of ¯am-ing. Those who ¯amed wrote more comments, on average, but they were generally irrelevant to the topic.
6. Conclusion
Group support systems may increase meeting ef®ciency, effectiveness, and satisfaction, but with anonymity come a few unwanted effects, such as ¯aming; i.e., comments written to offend others in the group. Warnings against such behavior may reduce their occurrence, but little is known about why they appear.
This study has investigated the affect of topic knowledge, importance, and level of controversy, along with familiarity with electronic communication, satisfaction with the meeting process, and gender on the incidence of ¯aming by individuals who have never used the system before. Only gender played a signi®cant role.
References
[1] M. Aiken, D. Hawley, Z. Min, H. Sloan, How to improve bank meetings, Journal of Retail Banking 16(4) (1994/1995) 21±25.
[2] M. Aiken, C. Hwang, J. Martin, A Japanese group decision support system, International Journal of Computer Applica-tions in Technology 9(5/6), 1996, pp. 233±238.
[3] M. Aiken, C. Hwang, J. Paolillo, L. Lu, A group decision support system for the Asian Pacific Rim, Journal of International Information Management 3(2), 1994, pp. 1±13. [4] M. Aiken, D. Kim, C. Hwang, L. Lu, A Korean group decision support system, Information & Management 28, 1995, pp. 303±310.
[5] M. Aiken, J. Krosp, A. Shirani, J. Martin, Electronic brainstorming in small and large groups, Information & Management 27, 1994, pp. 141±149.
[7] R. Albanese, D. Van Fleet, Rational behavior in groups: the free riding tendency, Academy of Management Review 10, 1985, pp. 244±255.
[8] R. Gallupe, A. Dennis, W. Cooper, J. Valacich, L. Bastianutti, J. Nunamaker, Electronic brainstorming and group size, The Academy of Management Journal 35(2), 1992, pp. 350±369. [9] S. Hiltz, M. Turoff, K. Johnson, Experiments in group decision making, 3: disinhibition, deindividuation, and group process in pen name and real name computer conferences, Decision Support Systems 5, 1989, pp. 217±232.
[10] J. Kayany, Contexts of uninhibited online behavior: flaming in social newsgroups on usenet, Journal of the American Society for Information Science 49(12), 1998, pp. 1135± 1141.
[11] S. Kiesler, J. Siegel, T. McGuire, Social psychological aspects of computer-mediated communication, American Psycholo-gist 39, 1984, pp. 1123±1134.
[12] F. Kitchens, Flaming in electronic media, Proceedings of the 29th Annual Conference of the Southwest Decision Sciences Institute, 3±7 March 1998, pp. 41±45.
[13] A. LaPlante, '90s style brainstorming, Forbes ASAP, 25 October 1993, pp. 41±61.
[14] M. Lea, R. Spears, Computer-mediated communication, de-individuation and group decision making, International Journal of Man-Machine Studies 34(2), 1991, pp. 283±302. [15] J. Nunamaker, A. Dennis, J. Valacich, D. Vogel, J. George,
Electronic meeting systems to support group work, Commu-nications of the ACM 34(7), 1991, pp. 40±61.
[16] B. Reinig, R. Briggs, S. Brandt, J. Nunamaker, The electronic classroom on fire: why it happens and how to put out the flames, Proceedings of the 30th Annual Hawaii International Conference on System Sciences 2, 1997, pp. 639±647.
[17] B. Reinig, R. Briggs, J. Nunamaker, Flaming in the electronic classroom, Journal of Management Information Systems 14(3) (1997/1998) 45±59.
[18] R. Rice, Computer-mediated communication system network data: theoretical concerns and empirical examples, Interna-tional Journal of Man-Machine Studies 32(6), 1990, pp. 627± 648.
[19] J. Siegel, S. Dubrovsky, S. Kiesler, T. McGuire, Group processes in computer-mediated communication, Organiza-tional Behavior and Human Decision Processes 37, 1986, pp. 157±187.
Milam Aiken received a BS in Engi-neering and an MBA from the University of Oklahoma, a BA in Computer Science and a BS in Business from the State University of New York, and a PhD in Management Information Systems from the University of Arizona. He is an Associate Professor of Management In-formation Systems at the University of Mississippi.
