service navigation

EASP – European Association of Social Psychology

Seedcorn Grant Report

01.12.2016, by Sibylle Classen in grant report

Stefan Pfattheicher, (Ulm University, Germany)
Motivational basis of social influence

The EASP seedcorn grant gave me the possibility to investigate the motivational basis of social influence. Beforehand, I want to thank the EASP for the valuable support that encourages me to conduct the research outlined in the following. The research was done in collaboration with Robert Schnuerch, Bonn University, Germany.
In our line of research, we build on the basic hedonic principle that individuals are generally motivated to approach pleasure and to avoid pain, and that they regulate their current state according to this principle (e.g., Higgins, 2012). In this regard, some types of human behavior are obviously regulated based on approach and avoidance, such as decisions in economic games, where gains and losses are usually salient and central (Scheres & Sanfey, 2006). For other facets of behavior, however, it is less obvious whether and how they are guided by the prospect of reward and punishment. This seems to be the case with socially influenced behavior, which is highly prevalent and, thus, of particular theoretical and practical relevance in everyday life (for reviews, see Bohner & Dickel, 2011; Cialdini, 2006; Cialdini & Goldstein, 2004; Cialdini & Trost, 1998; McDonald & Crandall, 2015; Wood, 2000). It is well-established that individuals yield to social influence driven by certain goals (Cialdini & Goldstein, 2004; Wood, 2000; see also Campbell & Fairey, 1989; Deutsch & Gerard, 1955). In this regard, one can ask the question whether individuals typically align their own behavior to others to avoid social punishment (the disapproval of others) or to approach social reward (a positive reputation for one’s actions).
This central question was investigated in two contexts: First, in the context of the watching eyes phenomenon reflecting the finding that individuals are not only influenced by the actual presence of others but also when merely a subtle cue of being watched (i.e., stylized watching eyes) is present in the environment (Pfattheicher & Keller, 2015). Second, social influence was investigated in the context of decision-making when individuals adopt a peer group’s judgments during perceptual decision-making. The central question was examined by means of neurophysiological recordings, namely electroencephalography (EEG). EEG allows monitoring directly the current motivational orientation by assessing frontal cortical asymmetry on-line (for a review, see Harmon-Jones, Gable, & Peterson, 2010; Harmon-Jones, Lueck, Fearn, & Harmon-Jones, 2006).
Regarding the watching eye phenomenon, recent research has shown prosocial effects of subtle cues of being watched on several facets of human behavior such as bicycle theft (Nettle, Nott, & Bateson, 2012) and littering (Ernest-Jones, Nettle, & Bateson, 2011; notice published null effects by several authors, cf. the meta-analyses of Nettle, Harper, Kidson, Stone, Penton-Voak, & Bateson, 2013, and Sparks & Barclay, 2013). Remarkably, research on cues of being watched shows that subtle watching eyes influence humans’ behavior in situations in which their behavior cannot be traced back to the person, that is, subtle cues of being watched influence humans’ behavior in completely anonymous situations.
In a first study, we created a paradigm that allows recording of EEG while participants complete a task that tested the watching-eyes phenomenon. The applied paradigm built on recent work by Ofan, Rubin, and Amodio (2014) who showed that individuals process black and white faces differently in dependence of whether they were told that their responses to these faces were observed or not. Congruently, individuals’ processing and judgments of these faces should be affected when a subtle cue of being watched is presented (vs. not presented).
Ofan and colleagues (2014) used pictures of ten white male faces and ten black male faces that were equated on luminance and contrast, thus holding these parameters constant (which is important in EEG research). These pictures were also used in our study, and the persons displayed on these pictures were judged on several (prejudice affected) dimensions, that is, how likely they are trustworthy, intelligent, poor, violent, and athletic (cf. Devine, 1989).
The judgments were made in block trials: First, participants were asked to judge ten white males and ten black males regarding their trustworthiness. Specifically, a picture of a face emerged on a computer screen for 300 ms (cf. Ofan, Rubin, & Amodio, 2011). On the next screen, participants were asked about the trustworthiness of the person. In order to prevent conscious regulation of social desirability, participants were asked to make this decision as fast as possible. When the twenty persons were judged regarding their trustworthiness, the next dimension (intelligence) was in focus. That is, all black and white persons were judged regarding their intelligence (after that athletics, and so on). In sum, participants made 100 judgments (20 pictures × 5 dimensions).
Crucially, participants were randomly assigned to one of two conditions: the Eye Cue Condition or the Control Condition. In the Eye Cue Condition, the computer screens (i.e., when the faces were perceived as well as when the judgment was made) were headed by stylized eyes (Keller & Pfattheicher, 2011). In the Control Condition, two plain stars (in Times New Roman font) of the same total size as the social cues were presented (see Pfattheicher & Keller, 2015; Powell et al., 2012).
Given that subtle cues of beings watched increase socially desirable tendencies (Nettle et al., 2013; Pfattheicher & Keller, 2015) while prejudice is socially undesirable (e.g., Devine, 1989), it was hypothesized that participants’ judgments are less prejudiced when a subtle cue of being watched is presented (vs. not presented). Before applying cost intensive EEG, we pre-tested this paradigm. However, there were no significant effects of the watching eyes on participants’ judgments. Therefore, we did not proceed with recoding EEG in this paradigm. Instead, we shift towards the context of decision-making when individuals adopt a peer group’s judgments during perceptual decision-making.
In this study, participants first read instructions on-screen, learning that their task would be to listen to different tones and spontaneously decide whether each tone’s pitch was higher or lower than the reference tone. At the beginning of the task, they repeatedly listened to the reference tone and were asked to memorize it. Every 30 trials, the reference tone was presented several times as a reminder. Importantly, participants read an untruthful cover story indicating that during the previous semester, several students had performed this task and had given written consent to have their judgments recorded and shown to other participants. Of these previous participants, three had been selected at random. During the experiment, the judgments of these three previous participants would be displayed before each tone. Crucially, we ran two different conditions to be able to differentiate between adjustment effects that were actually socially induced and those that represented less specific, presumably low-level effects such as priming (Germar, Albrecht, Voss, & Mojzisch, 2016; Germar, Schlemmer, Krug, Voss, & Mojzisch, 2014). One half of the experiment began with an alert saying/indicating that from now on, all group responses were matched with the tones. Thus, majority responses were highly relevant seeing as any group judgment ostensibly pertained to the exact upcoming tone that participants subsequently had to judge (experimental condition). The other half of the experiment began with an alert informing participants that all of the group’s responses had been randomized such that the display of group judgments was highly unlikely to pertain to the upcoming tone, making majority responses completely irrelevant (control condition). The order of these two conditions was counterbalanced across participants (i.e., a within-design was applied).
Using resting electroencephalography (EEG) prior to the task just described, we can show that frontal asymmetry is predictive of the tendency to yield to social influence: Stronger right- than left-side frontolateral activation during a resting-state session prior to the experiment was robustly associated with a stronger inclination to adopt a peer group’s judgments during perceptual decision-making in the experimental but not in the control condition. Frontal cortical asymmetry has long been established as a valid biomarker of motivational direction and, based thereupon, a reliable predictor of motived behavior (Harmon-Jones, 2003). We demonstrate for the first time that rightward frontolateral asymmetry at rest predicts the tendency to adjust one’s behavior to peer-group influence. We posit that this reflects the role of a person’s chronic avoidance orientation in socially adjusted behavior. To test this notion from another perspective, we are currently analyzing two studies in which chronic individual differences in avoidance motivation and social conformity were assessed.


  • Bohner, G., & Dickel, N. (2011). Attitudes and attitude change. Annual Review of Psychology, 62, 391-417.
  • Campbell, J. D., & Fairey, P. J. (1989). Informational and normative routes to conformity: The effect of faction size as a function of norm extremity and attention to the stimulus. Journal of Personality and Social Psychology, 57, 457-468.
  • Cialdini, R. B. (2006). Influence: The psychology of persuasion (3rd ed.). New York, NY: Collins.
  • Cialdini, R. B., & Goldstein, N. J. (2004). Social influence: Compliance and conformity. Annual Review of Psychology, 55, 591-621.
  • Cialdini, R. B., & Trost, M. R. (1998). Social influence: Social norms, conformity and compliance. In D. T. Gilbert, S. T. Fiske, & G. Lindzey (Eds.), Handbook of social psychology (pp. 151-192). New York, NY: McGraw-Hill.
  • Deutsch, M., & Gerard, H. B. (1955). A study of normative and informational social influences upon individual judgment. Journal of Abnormal and Social Psychology, 51, 629-636.
  • Devine, P. G. (1989). Stereotypes and prejudice: Their automatic and controlled components. Journal of Personality and Social Psychology, 56, 5-18.
  • Ernest-Jones, M., Nettle, D., & Bateson, M. (2011). Effects of eye images on everyday cooperative behavior: A field experiment. Evolution and Human Behavior, 32, 172-178.
  • Germar, M., Albrecht, T., Voss, A., & Mojzisch, A. (2016). Social conformity is due to biased stimulus processing: Electrophysiological and diffusion analyses. Social Cognitive and Affective Neuroscience, 11, 1449-1459.
  • Germar, M., Schlemmer, A., Krug, K., Voss, A., & Mojzisch, A. (2014). Social influence and perceptual decision making: A diffusion model analysis. Personality and Social Psychology Bulletin, 40, 217-231.
  • Harmon-Jones, E. (2003). Clarifying the emotive functions of asymmetrical frontal cortical activity. Psychophysiology, 40, 838-848.
  • Harmon-Jones, E., Gable, P. A., & Peterson, C. K. (2010). The role of asymmetric frontal cortical activity in emotion-related phenomena: A review and update. Biological Psychology, 84, 451-462.
  • Harmon-Jones, E., Lueck, L., Fearn, M., & Harmon-Jones, C. (2006). The effect of personal relevance and approach-related action expectation on relative left frontal cortical activity. Psychological Science, 17, 434-440.
  • Higgins, E. T. (2012). Beyond pleasure and pain: How motivation works. Oxford: Oxford University Press.
  • Keller, J., & Pfattheicher, S. (2011). Vigilant self-regulation, cues of being watched and cooperativeness. European Journal of Personality, 25, 363-372.
  • McDonald, R. I., & Crandall, C. S. (2015). Social norms and social influence. Current Opinion in Behavioral Sciences, 3, 147-151.
  • Nettle, D., Harper, Z., Kidson, A., Stone, R., Penton-Voak, I. S., & Bateson, M. (2013). The watching eyes effect in the Dictator Game: It's not how much you give, it's being seen to give something. Evolution and Human Behavior, 34, 35-40.
  • Nettle, D., Nott, K., & Bateson, M. (2012). ‘Cycle thieves, we are watching you’: Impact of a simple signage intervention against bicycle theft. PloS one, 7, e51738.
  • Ofan, R. H., Rubin, N., & Amodio, D. M. (2011). Seeing race: N170 responses to race and their relation to automatic racial attitudes and controlled processing. Journal of Cognitive Neuroscience, 23, 3153-3161.
  • Ofan, R. H., Rubin, N., & Amodio, D. M. (2014). Situation-based social anxiety enhances the neural processing of faces: Evidence from an intergroup context. Social Cognitive and Affective Neuroscience, 9, 1055-1061.
  • Pfattheicher, S., & Keller, J. (2015). The watching eyes phenomenon: The role of a sense of being seen and public self-awareness. European Journal of Social Psychology, 45, 560-566.
  • Powell, K. L., Roberts, G., & Nettle, D. (2012). Eye images increase charitable donations: Evidence from an opportunistic field experiment in a supermarket. Ethology, 118, 1096-1101.
  • Scheres, A., & Sanfey, A. G. (2006). Individual differences in decision making: Drive and reward responsiveness affect strategic bargaining in economic games. Behavioral and Brain Functions, 2, 1-8.
  • Sparks, A., & Barclay, P. (2013). Eye images increase generosity, but not for long: The limited effect of a false cue. Evolution and Human Behavior, 34, 317-322.
  • Wood, W. (2000). Attitude change: Persuasion and social influence. Annual Review of Psychology, 51, 539-570.