In everyday life discussion, people try to persuade each other about the goodness of their viewpoint regarding a certain topic. This persuasion process is usually affected by several elements, like the ability of the speaker in formulating logical arguments, her confidence with respect to the discussed topic, and the emotional solicitation that certain arguments may cause in the audience. In this study, we compare the effect of using one of the three well-known persuasion strategies (Logos, Ethos and Pathos) in the argumentation process. These strategies are used by a moderator who influences the participants during the debates. We study which persuasion strategy is the most effective, and how they vary according to two mental metrics extracted from electroencephalograms: Engagement and workload. Results show that the right hemisphere has the highest engagement when Logos arguments are proposed to participants with Neutral opinion during the debate. We show also that the Logos strategy solicits the highest mental Workload, and the Pathos strategy is the most effective to use in argumentation and to convince the participants.
In everyday life, arguments are “reasons to believe and reasons to act”. Argumentation is the process by which arguments are constructed and handled. Thus argumentation means that arguments are compared, evaluated in some respect and judged in order to establish whether any of them are warranted. Argumentation is the process by which arguments are constructed and handled in a debate. As explained by Mercier and Sperber , the function of reasoning is argumentative. It is to devise and evaluate arguments intended to persuade. A key feature of argumentation is that of being rational and grounded on logical inferences so that it can support critical thinking. However, in recent years, some approaches [4,5,6,7,8] have highlighted that argumentation is not a purely rational process but it involves past experience and emotions . Despite the number of contributions studying either the link between emotions and persuasive argumentation from the theoretical point of view (e.g., ) or the reasoning attitude evolution when persuasive arguments are presented to users from an empirical point of view (e.g., ), none of these approaches tackles the problem of studying the link between persuasive argumentation and emotions in an empirical setting. In this paper, we address this issue through the study of the correspondences between arguments, the adopted persuasion strategy, and the emotions measured using Electroencephalograms (EEG). We designed an experiment where 5 participants interact with each other by debating about a certain topic provided by a moderator. One of these participants, called the persuader (PP), plays a specific persuasion strategy (Ethos, Logos, Pathos) in order to convince the others about the goodness of her point of view.
The remainder of the paper is organized as follows. In Sect. 2, we describe the experimental setting in which our empirical evaluation took place, and the three hypotheses we formulated. Section 3 discusses the obtained results with respect to the three hypotheses. Conclusions end the paper.
2 Experimental Settings
The experiment was distributed over 5 sessions of 4 participants: 20 participants (7 women, 13 men, all right handed and students from the University of Montreal) plus PP, a fictive participant in charge of triggering the persuasion strategy. Participants argue in plain English proposing arguments, which are in favor or against the arguments proposed by the other participants. During these debates, participants are equipped with emotions recognition tools, recording their emotions.
2.1 Persuasion Strategies
During the debate, participant PP adopted one of the following three persuasion strategies :
Logos: logic and rationality are highly valued, and this type of persuasion strategy relies on the use of rational arguments following from logical inferences.
Ethos: if we believe that a speaker has good sense, good moral character, and goodwill, we are inclined to believe what that speaker says, and this type of persuasion strategy underlines that the speaker has the appropriate expertise or authority to speak knowledgeably about the discussed topic.
Pathos: emotions such as anger, pity, fear, and their opposites, powerfully influence humans’ rational judgments, and this type of persuasion strategy is directed toward moving the emotions of the debaters.
2.2 Argumentation Model
In order to model the textual debates we collected during the experiment and study them from the argumentation point of view, we rely on abstract bipolar argumentation [10, 11] where we do not distinguish the internal structure of the arguments (i.e., premises, conclusion), but we consider each argument proposed by the participants in the debate as a unique element, then analyzing the relation it has with the other pieces of information put forward in the debate. In particular, in bipolar argumentation two kinds of relations among arguments are considered: the support relation, i.e., a positive relation between arguments, and the attack relation, i.e., a negative relation between arguments.
2.3 Emotion Detection Tools
Each participant was equipped with the following sensors:
1 Camera to detect facial expressions.
1 EEG headset (associated to engagement/workload indexes detection system).
1 EDA bracelet to assess stress.
1 Eye-tracker to collect gaze data.
2.4 Cognitive Measures
In this study, we have used two cognitive measures based on EEG physiological data:
Engagement Index: refers to the level of attention and alertness during a task . The engagement index [14,15,16,17] is computed from three EEG frequency bands: α(8–12 Hz), β(12–22 Hz) and θ(4–8 Hz): Engagement = β/(α + θ). This index is computed each second from the EEG signal. To get Left and right engagement indexes, we calculated two averages for each frequency band (α, β and θ) one from the seven sensors located on the left side of the Emotiv headset and the other from the right side.
Workload Index: refers to a measurable quantity of information processing effort performed by a person on a task. The mental workload is generally related to the level of information loading in the working memory during a task. The EEG workload index was based on pre-trained predictive model . This model was trained using a set of EEG data collected from a training phase during which a group of seventeen participants performed a set of brain training exercises and were asked to report their workload level using the subjective scale of NASA Task load index . The evaluation of this model showed a correlation with the participants’ subjective scores NASA TLX reaching 82%.
Phase 0: Pre-selection phase where the participants fill in an online form about their initial opinion on all the topics, then for each debate two participants pro and two con were selected;
Phase 1: Receiving the participants in the experimental room and installing the sensors on them;
Phase 2: Two 15 min debates session in which:
An animator introduces the topic to be discussed and asks opinions;
Each participant exposes his/her opinion, and comments on the others’ opinions;
PP plays a persuasion strategy, and posts arguments trying to bring participants with opposite viewpoints to the targeted position;
Phase 3: Opinion change self-report.
(H1) Logos arguments solicit one side of the brain, while pathos and ethos arguments solicit different brain sides.
(H2) The most effective persuasion strategy is Pathos, even if the participants do not completely reverse their opinion about the debated topic.
(H3) Logos arguments induce higher workload in the debates, while pathos and ethos arguments induce higher engagement.
In order to verify the three hypotheses detailed above, we have analyzed the collected data by dividing the debate into three phases: the introduction (Introduction), the argumentation (Argumentation) and the conclusion (Conclusion). In the Introduction phase, participant PP takes a position with regard to the topic of the debate justified with a general statement to support his point of view. In the Argumentation phase, participant PP tries to convince the other participants of the relevance of his opinion by adopting one of the three persuasion strategies (Logos, Ethos or Pathos) to formulate his arguments. In the Conclusion phase, PP point out his final position with an invitation to the other participants to support him. As we are interested in the impact of PP’s arguments, we considered the participants’ physiological reactions during the 10 s after each PP intervention in the debates. A repeated-measures design for each debate phases was used where average engagement and workload indexes were evaluated for each participant.
To verify these hypotheses, we have computed workload and engagement indexes for each participant. We have run repeated-measure analysis of variance (repeated measure ANOVA) using IBM SPSS statistic software V24 for computing the differences of mean engagement for each brain side for 10 s after PP’s intervention.
To verify H1 and H2, we have run the repeated measure ANOVA to evaluate the effect of PP’s arguments on the engagement index of each brain hemisphere with regards to the participant final position with respect to participant PP’s one (Neutral, Opponent or Supporter). So, for this analysis, the within-subject factor is Debate_phases (Introduction, Argumentation and Conclusion) and the between-subjects factors are: PP_strategy (Logos, Ethos and Pathos), Brain_sides (Left and Right) and Final_Position (Neutral, Opponent or Supporter).
3.1 Hypothesis H1
The engagement means of the Left and Right brain hemispheres with regard to the final position of the participant are presented in the descriptive statistics table below (Table 1). The persuasion strategies’ mean of engagement in each brain hemisphere are compared for each debate phase depending on the final position to the PP’s opinion.
To validate the repeated-measures of ANOVA, we used a Mauchly’s test for sphericity on the dependent variable “debate phases” (sig = .000). According to this test, we assess the significance of the corresponding F with Greenhouse-Geisser correction. So, for the within-subject effect test by applying Greenhouse-Geisser correction, we have a significant effect of debate phases on engagement with F(1.146,73.346) = 3.425 and p = 0.036. We have similarly significant interaction of Debate_Phases*PP_Strategy with F(2.292, 73.346) = 3.179 and p = 0.041 that means significant effect on engagement.
By checking Levene’s testFootnote 1 for homogeneity of variance, we found that variances are homogeneous for the Conclusion phase (F(15,64) = 1.328 and p = 0.213) and not for the Introduction and Argumentation ones (respectively, F(15,64) = 2.753, p = 0.003 for Introduction and F(15,64) = 2.028, p = 0.027 for Argumentation). The between-subject effects results show that there is significant main effects of the factor Brain_Sides on engagement, F(2,64) = 8.792, p = 0.004, also for the factor Final_Position on engagement, F(2,64) = 5.452, p = 0.007 and then PP_strategy on Engagement, F(2,64) = 5.116, p = 0.009. There is also significant main effect of the factors interaction PP_Strategy*Final_Position on engagement, F(3,64) = 5.452, p = 0.000. However, for the three factors interaction Brain_sides*PP_strategy*Final_Position shows no significant main effect with a good F value (F(3,64) = 2.098, p = 0.109) which means that there is an influence of these 3 factors on engagement but it is not statistically significant.
Figure 1 shows the means of engagement in the brain hemispheres by debate phases for the different persuasion strategies used by PP participant. In order to better understand what’s going on in the debates, we focused on the participants’ Final position towards participant PP targeted opinion (Fig. 2). In fact, the participants who stayed Neutral all over the debates had the highest engagement in both brain sides, but those who tacked position as opponents or supporters of PP’s opinion had lower engagements in both brain sides. So participants who have not decided about the PP’s opinion were more engaged in looking for the reasons about why that opinion could be right or not. As we can see in Fig. 2, the right hemisphere has generally higher engagement scores. So participants were more relaying on their intuition, imagination and feelings to evaluate PP’s arguments.
Comparing Figs. 1 and 2, we can see that the Right Hemisphere (Fig. 1-B) shows high engagement when dealing with Logos arguments, similarly to participants who have Neutral position during the debate (Fig. 2-B).
For those participants who have taken a decision (Opponents or Supporters, Fig. 2), we may note that the mean engagement is almost the same between the three debates’ phases (between 0.85 and 1.15 for the Right brain side, and between 0.60 and 0.85 for the Left brain Side), whereas in Fig. 1 for the Pathos strategy the mean engagement is the lowest. Logos Engagement is significantly higher in the Argumentation phase compared to the Introduction phase in the Right brain. Participants are using their intuition to evaluate the Logos arguments of PP but they cannot decide so they stay in the Neutral position. Logos arguments need to be treated analytically to lead to some kind of decision making. Engagement for Ethos and Pathos arguments are more similar to the engagement of the participants that have taken a decision (Supporter or Opponent) with respect to PP’s arguments.
For the participants who were Neutral, Fig. 2 shows that the mean engagement is always higher than 1.15 for the Right Side, and 0.85 for the Left Side. However, we may note that for the Ethos strategy, the Right engagement is high in the Introduction phase and falls down in the Argumentation phase. While for the Logos and Pathos strategies, the engagement is lower in the Introduction and goes up in the Argumentation and Conclusion phases, for Right Hemisphere the engagement goes significantly higher.
This result is justified by the simple effect analysis showing a significant mean difference of Right Engagement between Argumentation and Introduction phases with Ethos strategy (Mean difference = −.180, p = .024) and also Logos Strategy (Mean difference = .432, p = .000) but there is near significant difference for the Pathos strategy in the Left engagement (Mean difference = .134, p = .067).
The significant link to the right brain is pretty clear. The specialized characteristics of the right hemisphere make it the seat of curiosity, synergy, experimentation, global thinking, flexibility and feelings. Every one of these characteristics is capable of enhancing an individual’s thinking to find a counter example or to make inferences and decisions. For example, an intuitive idea that pops into a person’s mind, just after a Logos argument, can lead to accept or refute the others’ opinion. That’s the right hemisphere part. Now, taking a decision about the opinion requires different specialized mental processes, and these are located in the left hemisphere. Diagnosing the proposed argument to decide whether we support it or not, makes use of our rational processes of analysis and logic (Fig. 3).
Since the right hemisphere and the left hemisphere are interconnected through the corpus callosum, it is then possible to iterate back and forth between these modes to arrive to make a decision. The left brain helps keeping the right brain on track during the debate.
3.2 Hypothesis H2
To verify the second hypothesis, about the effectiveness of persuasion strategies to get more supporters, we have run simple effects analysis comparing the three factors interaction: Debate_Phase*PP_strategy*Final_Position with the factor Debate_Phase. To get this supplementary analysis, we have added this instruction in the SPSS script:
/EMMEANS = TABLES(DebatePhase*PP_strategy*Final_position) COMPARE (DebatePhase)
Looking at Fig. 4, we get an idea about the different persuasion strategies mean engagement throughout the debate phases classed by final positions as Supporter, Opponent or Neutral with respect to PP’s opinion.
For the Supporters, Fig. 4-C shows that the global engagement is higher for Ethos compared to the other strategies. In fact, there is a decrease of engagement (from 1.5 to 1.2) between the Introduction and Argumentation phases for the supporters, with Ethos strategy. For the other strategies, the supporters have almost the same engagement (⋍0.7) during the debate phases except for Pathos it increases to 0.9 in the Conclusion phase. By looking at the simple effect comparison, we also found that the significant mean differences of engagement are between the Introduction and Argumentation phases for Ethos strategy (Mean difference = .293, p = .000) and of Engagement between Argumentation and Conclusion phases for Pathos strategy (Mean difference = .238, p = 0.056). This decreasing and low engagement shows that there is low resistance to PP’s arguments from the Supporters.
For the Opponents, Fig. 4-B shows that for Ethos strategy the engagement is lower compared to what we have seen for the Supporters in the Ethos strategy. We notice that the opponents’ engagement is almost the same (0.85) during the debate and it goes a little bit lower in the Argumentation phase. This means that the opponent rejects PP’s argument from the beginning of the debate and does not believe him during the debate as an expert or scientific (or does not have confidence in the provided scientific results). For Logos strategy, the Opponent’s Engagement starts from 0.77 and increases a little bit in the Argumentation phase (0.86) but it goes down again till 0.76. This engagement increase may be due to the mental effort in evaluating the arguments and their logical consequences. At the end the engagement goes down because the participant was not convinced with the logical reasons presented by PP. For the Pathos strategy, the Opponent’s engagement is still increasing from 0.72 at the Introduction phase, to 0.90 at Argumentation phase, and reaches 1.15 in the Conclusion. Here we have near significant difference for the Pathos strategy between Introduction and Argumentation (Mean difference = .169, p = .072). We note that the engagement of the Opponents remains increasing for Pathos unlike the other strategies where it was relatively low and stable due the rejection from the beginning for the Ethos arguments or the logical weakness of the arguments for Logos during the Argumentation phase. This increasing Engagement shows us the mental resistance to change form Opponent to Supporter. This proves that the Pathos strategy is the most difficult to reject because it connects with people’s emotional side.
For the Neutral Participants, Fig. 4-A shows that for Ethos the engagement is the lowest (0.5) compared to the other strategies and also with respect to the other final positions. Ethos may make people indifferent and disengaged in taking a position towards PP’s point of view. For the Logos strategy the participant’s engagement is the highest compared to the other strategies and also to the other final positions and remains increasing from 1.5 at the Introduction phase to 2.50 at the Argumentation phase and reaches 3.0 in the Conclusion. In the simple effect comparison, we also found a significant mean difference of engagement between the Introduction and Argumentation phases (Mean difference = −.685, p = .000) and between Argumentation and Conclusion (Mean difference = −.441, p = .010) for the Logos strategy. Logos may make people undecided till the end of the debate, and engaged in intuitively evaluating the validity of PP’s arguments. Moreover, since they do not have the time to verify analytically the argument they tend to not take a position with respect to PP’s point of view. We notice that there are no Neutral participants for the Pathos strategy. This shows that the Pathos strategy makes people decisive about their point of view even by supporting or rejecting the other’s arguments because Pathos touches people emotionally and makes them remember their past experiences.
3.3 Hypothesis H3
For the third hypothesis, we studied the tendencies of the participants’ workload and engagement with respect to PP’s argumentation strategy. We have extracted the engagement and the workload indexes for the 10 s after PP intervention to verify their evolution through the debate phases and get an idea about which strategy elicits more workload and engagement.
To verify this Hypothesis, we have run the repeated measure ANOVA to measure the effect of PP’s arguments on the engagement and workload indexes with regards to the participant’s final position with respect to participant PP (Neutral, Opponent or Supporter). So for this analysis, the within-subject factor is debate phases (Introduction, Argumentation and Conclusion) and the between-subjects factors are: PP_strategy (Logos, Ethos and Pathos), Measures (Engagement and Workload) and Final_Position (Neutral, Opponent or Supporter).
For the within-subject effect test by applying Greenhouse-Geisser correction, we did not find significant effects. We found a good factors interaction of: Debate_Phase*Measure*PP_strategy with p = 0.280 and F(2.447, 78.294) = 1.300 (Mauchly’s test for sphericity on the dependent variable “debatePhase”: sig = .000). By checking Levene’s test for homogeneity of variance, we found that variances are homogeneous for the Argumentation (p = 0.139, F(15,64) = 1.483) and Conclusion phase (p = 0.061, F(15,64) = 1.762) except for the Introduction (p = 0.012, F(15,64) = 2.274). The between-subject effects results show that there are significant main effects in the interaction Measure*Final_position*PP_strategy, F(3,64) = 5.415, p = 0.002.
Looking at Fig. 5, we get an idea about the different persuasion strategies’ mean Engagement and Workload throughout the debate phases. In order to better understand what was going on in the debates, we focused on the participants’ final position towards participant PP targeted opinion (Fig. 6).
In fact, the Neutral participants (Fig. 6-A) have Workload and Engagement similar to what we have in the Logos strategy (Fig. 5-B) where the Engagement decreases (from 0.9 to 0.8) in the Argumentation, and goes up to 0.87 in the Conclusion. Also the Workload is about 0.6 between Introduction and Argumentation phases and goes up to 0.67 in the Conclusion phase. The Ethos strategy induces more engagement at the Argumentation phase, and during the Conclusion phase the workload increases reflecting the fact that people’s memory is overloaded and they cannot handle such amount of information to make decisions. This leads at the end to Neutral state.
The workload and engagement of the Opponents (Fig. 6-B) are more similar to what we have in Pathos Strategy (Fig. 5-C) where the engagement increases (from 0.67 to 0.8) in the Argumentation phase and continue to increase till 1.05 in the Conclusion. For the workload in Pathos, it is about 0.6 between Introduction and Argumentation phases and decreases to 0.5 in the Conclusion. So Pathos makes more access to the memory in the Argumentation phase due to the emotional elicitation of the arguments and it decreases in the Conclusion while the engagement increases to take a position with respect to PP’s opinion which is more often as Opponent but it can be a supporter too.
Also for the Supporters (Fig. 6-C) their workload and engagement are very similar to what we have in the Ethos strategy (Fig. 5-A) where the engagement decreases (from 0.92 to 0.8) at Argumentation and goes up again to 0.88 at the Conclusion. Furthermore, the workload goes up from 0.55 at the Introduction to 0.59 in the Argumentation phase and increases to 0.62 in the Conclusion. So as PP presents himself as an expert or scientist leading less resistance to his arguments that is manifested as a decrease of the engagement index in the Argumentation phase but the workload index is going up all over the debate meaning that participants are accepting the information given by PP.
In this paper, we presented an empirical study to investigate the relations among the mental states of the participants in a debate and the persuasion strategies adopted in the argumentation process. This experiment highlights the important role of emotions in persuasive argumentation. We found that the different persuasion strategies solicit different sides of the brain. Logos arguments involve more workload of the participants while Pathos and Ethos strategies induce more engagement. Finally, Pathos resulted to be the most efficient strategy for convincing the participants to change their opinions.
Levene’s test is used to assess the equality of variances for a variable calculated for two or more groups.
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The authors acknowledge the supports from the SEEMPAD associate team project (http://project.inria.fr/seempad/), the FRQNT (Fonds de recherche Québec nature et technologie) and NSERC (National Science and Engineering Research Council).
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Benlamine, M.S., Villata, S., Ghali, R., Frasson, C., Gandon, F., Cabrio, E. (2017). Persuasive Argumentation and Emotions: An Empirical Evaluation with Users. In: Kurosu, M. (eds) Human-Computer Interaction. User Interface Design, Development and Multimodality. HCI 2017. Lecture Notes in Computer Science(), vol 10271. Springer, Cham. https://doi.org/10.1007/978-3-319-58071-5_50
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