ANALYSIS AND DISCUSSION

To begin the data analysis, the qualitative, open — ended responses were reviewed to confirm that the subjects were sufficiently engaged in the sce­nario and to identify any notable trends. Several observations surfaced:

1. Nearly all subjects responded with written feedback and in every case the message was sensible and earnest, showing an investment in the scenario that lends veracity and cred­ibility to the results, e. g.

“Due to John Doe’s Web presence, I feel that he would be a good team member since he seems to have the desire to be connected with friends and associates. Having a LinkedIn, account shows that he has contacts that have worked or are working in business environment. Plus, it seems that he has also created a Website for himself, which shows that he is technically savvy. ”

2. A small but noticeable minority of respon­dents expressed frustration that there was not enough information for them to feel comfortable with the decision (mostly for the ePersonas with no social networking presence) but this reinforces that they were invested in the scenario and reminds us that we are studying first impressions that don’t always lead to outcomes in and of themselves, e. g.

“There is nothing to assure that she is a good candidate for the team; therefore it would not be wise to base the decision on the information shown in the Google search results.”

3. Overwhelmingly, respondents did attend to social networking presence strongly and extrapolated that to various trait implica­tions, including those associated with the teammate decision, e. g.

“The search results show that he has strong social network connections. Therefore, he should be an active, sociable and energetic person. He seems to be teammate-material.”

4. A number of respondents derived surpris­ingly broad and strong negative character traits from the ePersonas that were essentially neutral, merely lacking social networking presence, e. g.

“Not outgoing, unsocial, shy, quiet, and keeps to himself.”

“The fact that there’s almost nothing out there about her… She seems like she probably doesn’t have much ambition or desire to do anything or accomplish anything.”

“Not social from the fact he doesn t use any SNS which is very strange these days.”

This suggests that at least some social network­ing presence may now be considered the norm with deviations leading to negative associations.

5. It was clear that in addition to the negative associations of too little social networking presence, there is a recognition that too much may be bad, at least in the project/teammate scenario, e. g.

“Thefact that she is on most ofthe social networks. I would want her on the team because of her people skills that she could possibly have; however, it makes me worry that she would spend too much time online rather than working on the project.”

“Jane doe would be a slacker. All of the pages describedfor this potential team mate were social sites, she wouldprobably get distracted easily and not be focused on getting work done.”

Based on the qualitative analysis then, it is clear that the data is reliable and reflects the intended manipulations. Further, the apparent strength of impact underscores the value of the research. In addition, the expectation of social networking presence and the sensitivity to the level or degree to which it appears in an ePersona raise unfore­seen issues informed by this study but needing further research.

The quantitative data were analyzed with respect to the research model and propositions, yielding additional insights from both expected and unexpected results. Standard statistical signifi­cance tests were applied for comparison of group mean pairs corresponding to the propositional statements.

The results are summarized in tables that list the experimental measures as rows and the vari­ous treatment group comparisons in columns. The equal sign (“=”) appears in cells where the means of the corresponding treatment groups (column) showed no significant difference (at the 0.05 confidence level) for that measure (row). For cells where significant differences were found, the group with the higher (always “better”) mean is indicated with an abbreviation followed by the “л” symbol (e. g. “MA” indicates a higher/better mean for males.) Some cells are shaded to highlight matches across columns for a given measure. The experimental measures (rows) include teammate desirability, the nine personality dimensions rel­evant to the task scenario as previously identified by Venkatsubramanyan and Hill (2007) and two additional measures: 1) Rating Confidence which captures the degree of confidence subjects felt in their decision and 2) the binary Yes/No decision to include the potential teammate represented by the ePersona, in the fictitious project team.

Table 1 relates to Proposition 1 which posited that both males (1a) and females (1b) would per­ceive target ePersonas including social networking presence more positively than those without. The proposition was based on relevant literature and the research model and indeed, the results support this expectation. Both female and male perceivers showed a preference for ePersonas with social networking presence across several dimensions.

Though there was some overlap between fe­males and males in the specific dimensions af­fected, there were even more dimensions where the two genders differed. Both male and female perceivers gave advantage to social networking personas in judging the Work with People and Curious dimensions. But females treated ePerso­nas similarly across four (4) additional dimensions (Desirability, Manage Multiple Tasks, Handle Conflict andAdapt to New Situations) while males did so for only one (1), Manage Anger, which was apparently not salient for females. And so males registered significant advantage for social net — workers across only three (3) dimensions, as opposed to six (6) for females, and yet, only the males showed significance in the Yes/No decision outcome measure, one that ostensibly reflects a comprehensive summation of desirability and the nine dimensions. This might be interpreted plau­sibly as males feeling more freedom to be decisive, even without delving as deeply and finding as much convincing evidence as the females, due to males’ confidence that they will have the power to control the outcome and diffuse any conse­quences that would possibly derive.

In any case, the overarching implication of Table 1 is that social networking presence does

make a difference, for perceivers of both genders, but in subtly different ways. Looking deeper, the next set of propositions explores how the target gender plays a role within the context of social networking presence or lack thereof for female perceivers (P2a/b).

Table 2, providing significance findings for female perceivers only, suggests a number of interesting observations with respect to Proposi­tions 2a and 2b, that female s will perceive female s more positively than males for targets without or with social networking presence. The leftmost two columns of results correspond to P2a and b, respectively, and show no support for either. No significant differences were found in comparing female to male targets without social networking presence (P2a). For ePersonas with social network­ing presence (P2b), significance was found only for a single dimension, Effective Team Member, and male targets were rated higher, not lower, as predicted in the proposition. This may owe to the overriding influence of established stereotypes when other cueing is indiscriminate as it was in this treatment with all targets showing social
networking presence equally (target gender was the only variable).

But the result is intriguing in that it surfaced only in the social networking presence treatment (P2b) and not in the treatment that was identical except for the absence of social networking pres­ence (P2a). The logical implication is an interac­tion effect-these female perceivers viewed male targets differently from female targets in the context of social networking presence only, at least on this single dimension-target gender and social networking presence effect differently when both are present than in the case of either alone. This is consistent with the observation from Table 1 that male and female perceivers view the value of social networking presence differently, but it adds a nuance-that those differences may further vary, depending on target gender, as suggested by Propositions P3a and P3b. To delve further into the interaction implications, the analysis explored how females viewed the added value of social networking for female as opposed to male targets (P3a), as seen in the rightmost two columns above.

The most notable point that surfaces is that female perceivers’ impressions were affected by social networking across more dimensions for male targets than for female targets. Significant effects from social networking were found only for three (3) of the ten dimensions for female targets (Work with People, Curious, and Adapt to New Situations). And the same three (3) dimensions showed significant effects for male targets but four (4) additional dimensions also show significant impact from social networking for the males, for a total of seven (7) affected among the ten (10) measured.

For male targets, these female perceivers’ impressions of the Desirability, Effective Team Member, Excellence and Manage Multiple Task dimensions showed significant positive effect from social networking that was not found in their perceptions of female targets where the sole difference was gender. This implies an interaction effect-the presence of social networking affects
females’ perception differently, and more compre­hensively for the males they are evaluating than the females. In other words, female perceivers give a greater social networking premium to males than females and/or penalize males more than females for the lack of social networking presence. Indeed closer inspection of the data suggests that it is a combination of both as the specific means for at least five (5) of the dimensions show a pattern of wider spread for the male targets-those with social networking outscore the social networking females while those without score lower than their female counterparts.

Thus, Table 2 provides convincing support for P3a and the existence of an interaction effect, for female perceivers, between target gender and so­cial networking presence. In this case, the female perceivers are clearly more affected by social networking presence in male ePersonas than in female ePersonas. Specifically the findings sug­gest that, for female perceivers, the stereotypical

view of males as less socially adroit than females is strongly reinforced when male targets lack social networking presence and this effect is excessively negative with respect to the non-social networking female targets. Interestingly, the positive effect of social networking presence on female perceivers’ impressions of male targets is so exaggerated that this same stereotype is strongly negated for male targets engaged in social networking, perhaps be­cause the elevated social investment is unexpected for males and defies the stereotypical view held by the females, even when compared to social networking females.

The obvious next question is whether the same phenomenon holds for male perceivers as examined in Table 3.

Table 3 replicates Table 2 but for male perceiv­ers and is interesting for similar reasons and by contrast with Table 2’s results for female perceiv — ers.

First, as with female perceivers, the leftmost two columns of Table 3 show that there is no sup­port for the propositions that males would show a target gender preference when ePersonas lack or include social networking presence (P2c and P2d, respectively). In contrast to the results for female perceivers however, there is no stereo­typical effect that gives the contrasting gender, female, an advantage in any dimension whether social networking presence is apparent or not.

In further similarity to female perceivers, male perceivers show some interaction effect between target gender and social networking presence so P3b is somewhat supported but this is far less pronounced than in the case of female perceiv­ers. For most of the ten (10) dimensions, there is no significant difference in their perceptions of either males or females, based on social network­ing presence. For one (1) of the ten dimensions, Work with People, significance is found both for male and female targets, so male perceivers are

consistent across target gender on this dimension (as are females according to Table 2).

For these male perceivers, then, the only tar­get gender differences due to social networking presence are found in Manage Multiple Tasks (advantage only for female targets), ManageAnger (advantage only for male targets), and Curious (advantage only for female targets). A difference is also found however, with advantage for males only, in the additional experimental binary mea­sure, the Yes/No decision, referring to the scenario task of choosing a teammate. Again, as with the similar result from Table 1, the implication is that male perceivers are more comfortable than female perceivers, making the choice decision based on less evidence, possibly due to greater confidence in their power to control the eventual consequences.

In summary, Table 3 suggests that for males, as for females, there is some interaction between
target gender and social networking presence. The effect is different however, from that for female perceivers in that it is not as consistent or as comprehensive across the range of impression dimensions. And yet, for male perceivers, it is seen in the Yes/No measure which intuitively would seem to encapsulate the range of dimensions in being the action outcome.

Table 4, comparing the significance findings from Tables 2 and 3, helps summarize and also highlights interesting contrasts.

Only for the Work with People dimension do male and female perceivers give social network­ing advantage to both male and female targets alike, though they both are consistent across target genders with respect to showing no sig­nificant social networking effect for three (3) other dimensions: Handle Conflict, Adapt to New Situations and Ability to Take Direction. Both also give social networking advantage to females
for Curious, but only female perceivers do so for male targets. Thus, we see again that there is some overlap and some difference in how male and female perceivers are impressed by social net­working, depending target gender. Target gender changes the way they both view social network­ing in ePersonas but in different ways and to different degrees. Perhaps the most interesting inconsistency is that, for the Manage Multiple Tasks dimension, male perceivers give a social networking advantage only to female targets while the reverse is true-female perceivers give it only to male targets. This is quite extraordinary and when combined with other gender differences identified above suggests some intriguing ideas about underlying phenomena.

We speculate that many of the observed differ­ences in the way males and females assign value to social networking presence by target gender are attributable to differences in the stereotypes upon which they draw and the central role of sociality in those stereotypes. Unlike impressions formed through rich engagements, such as face-to-face in­teraction, impressions formed from search results are based upon a relative paucity of informative cues. Yet, it appears that most subjects assigned significant influence to the available information and felt comfortable basing their selection deci­sions upon it. While one might wonder if subjects’ comfort with their decisions was due, in part, to the fictional nature of the decision context, sub­jects’ comments support the legitimacy of both the scenario and their decision-making processes. Indeed most subjects appeared to be invested and engaged in the task and comfortable making their decision based on search results. This we believe implies a quality unique to the Web-based form of impression formation-that perceivers over-attend to the information they find on the Web and feel unwarranted confidence in resultant decisions, probably due to an unfounded faith in the veracity of Web-based information and the misperceived sufficiency of search-based representations ofthat information. At the same time, the SIDE model, discussed above, suggests that these perceivers are likely falling back, however unconsciously, on gender stereotypes to supplement the sketchy information provided.

It follows then that stereotypes may play an exaggerated role in Web-based impression forma­tion and this study can be interpreted accordingly. For example, female perceivers gave benefit for social networking presence only to male targets on several of the measures and we suggest that this stems from the contradiction they saw between the evidence of social networking participation and their stereotypical view of males as less socially adept than females. This view, exaggerated by the lack of other individuating information, may have led females to over-reward males who were perceived to defy the stereotype based upon their social networking activity. Additionally, females penalized males more than females for lacking social networking presence across a number of factors, further supporting this interpretation-the lack of social networking presence reinforced the stereotypical female view of males as socially deficient and led to the disproportionate denigra­tion of the “socially lacking” males.

The fact that this phenomenon was not observed for male perceivers makes sense in light of the specific social networking context of this study and the way it relates to gender-based stereotypes. A lack of social aptitude is a major component of females’ stereotypical view of males and thus the selection decisions of female subjects were more influenced by the social networking presence, or the lack thereof, for males than for females. But if males indeed have lower social awareness, then sociality may play a less influential role in males’ stereotyping of others and thus may leave their selection processes less affected by social networking presence. This suggestion is consistent with the findings reported Table 3 above. If one were to replicate this experiment, focusing on a more influential dimension of males’ stereotypical views of females than sociality, then we might expect to see the same phenomenon-a stronger effect of their stereotypes coming through in their ratings of females than for males.

So it may be that Web-based impression for­mation is more susceptible to gender bias than are more traditional modes of impression forma­tion and the effect may be stronger. “Googling” someone may give a false sense of confidence, leading perceivers to believe they know they know “enough” to make a selection decision as their lim­ited knowledge of a target is likely supplemented, however unconsciously, by stereotypes. If this is indeed the case, this is a hazard of life in the digital domain best addressed through awareness and understanding.

CONCLUSION

In summary, the data lend support to some of the propositions and suggest some interesting nu­ances in the similarities and differences between male and female perceivers and the way their ePerception is affected by target gender, social networking presence, and interactions between the two. Previous research identifying the ef­fects of social networking presence and perceiver gender were further substantiated and extended to incorporate ePersona gender and the analysis surfaced intriguing phenomena.

Specifically this study found that both males and females tend to perceive a potential teammate with social networking activity more favorably than one without. However, results also indicate that males and females perceive and assign that social networking benefit differently. Female perceivers in our study viewed those engaged in social networking sites as more curious and desirable and more capable of multi-tasking, handling conflict, adapting to new situations and interacting well with others than those with no involvement in social networks. Meanwhile, male perceivers viewed social networking activity as an indication that a potential teammate is more curious, better able to manage anger and more likely to work well with others. These findings offer support for Proposition 1b and some support for Proposition 1a.

Our findings also suggest that social network­ing activity is a more influential factor than is target gender as neither male nor female perceiv — ers significantly preferred one gender over the other when controlling for targets’ involvement in social networks. Therefore we find no support for Propositions 2a-2d.

There does appear however, to be an interaction effect between target gender and social networking presence. Female perceivers showed a preference for male targets with social networking presence over males without social networking presence on seven of the ten assessed characteristics and a preference for social networking females on three of the target characteristics. Of particular interest is that female perceivers appear to assign a greater value to the social networking activities of male targets than that of female targets and assign a greater penalty to non-social networking males than they do to non-social networking females. This finding supports Proposition 3a.

Male perceivers also had more favorable impressions of those with social networking activity, scoring social networking males more favorably than non-social networking males on three characteristics and scoring social network­ing females higher than non-social networking females on three characteristics. Thus there does appear to be some support for Proposition 3b however the interaction effect of target gender and social networking activity is not as strong for male perceivers as it is for female perceivers.

These findings hold implications for practice, pedagogy and further research. For managers, the observed interaction for perceivers ofboth genders (especially females) between social networking presence and target gender (same as perceiver or different) amounts to a bias that may distort impressions of job applicants, for example, and could lead to sub-optimal hiring decision outcomes in the workplace. In particular, hiring supervisors should recognize the benefits and penalties a female interviewer may place upon male appli­cants based solely upon their social networking activities. Although the student-based subject pool admittedly limits the degree of generalizability to professional environments, one can argue that these individuals are no more than a year or two away from entering the workforce and they may be expected to carry their biases with them into positions where they will evaluate potential job applicants for their work teams. It thus behooves them, and their future managers, to develop an awareness of their biases with the aim of mini­mizing them and/or compensating for them in their decisions. And it behooves job applicants to be aware of them, particularly the strong nega­tive reactions to the lack of social networking presence, but also the sensitivity to excessively high levels of such activity, as evidenced in the qualitative responses, and to consider tuning their ePersonas accordingly, to the extent possible, when job seeking.

Findings concerning individuals’ use and valu­ation of social networking activity in impression formation hold implications for instructors as well. This study suggests that Web-based information may well play a role in students’ selection of teammates for class-based team projects be they face-to-face teams in traditional classrooms or virtual teams in online courses. The availability of such influential information on the Internet may be particularly problematic for instructors looking to minimize students’ preconceived opinions of potential teammates based upon factors such as social networking activity, which may play little or no role in the ability of a student to contribute meaningfully to a group. Although our sample was limited to business students, our findings may apply to other student groups as well given that most Millennials (a term often used to label those born roughly between 1980 and 2000) are technically savvy and it is arguable that no one group within this generation is any more or less likely to turn to the Internet for information when making such selection decisions.

While this and similar studies have shed some light upon the impacts of social networking activ­ity on our perceptions of others, many questions regarding the role of Web-based information in impression formation remain unanswered. Fo­cusing specifically on social networking, some extensions of this study would entail exploring the question of how much social networking presence is beneficial (or detrimental), the consequences of possessing a common name or sharing a name with a celebrity (making it hard to disambigu­ate the right identity), and the role of perceiver characteristics beyond gender on the impressions formed. Future research could also investigate the same research questions posed by our study to determine if the findings indeed apply to other populations such as professionals, non-business majors, and non-Milliennials.

Additionally, there remains the larger ques­tion of how Web-based searches fundamentally “change the game” in impression formation, as speculated in the discussion above. Based on the results ofthis study, we speculate that ePerceivers may tend to read more into search results than they should, relying on gender stereotypes (and possibly others) and thereby introducing greater bias into their impressions than they would in face-to-face contexts. Of course, this phenomenon is likely still evolving as the Web generation matures and users become savvier about the reliability, quality and quantity of Web-based information and as society’s stereotypical views of males and females shift over time. And indeed some of the behaviors and perceptions that underlie those stereotypes may themselves be expected to be fundamentally transformed by Web-based phenomena such the social networking revolution. The evolution of these phenomena will create moving targets that provide challenging but important opportunities for future research that further investigates the impact and formation ofWeb-based impressions.

ACKNOWLEDGMENT

We thank the reviewers and editors for their insights and assistance with this manuscript. This research was supported by the Behavioral Research Group ofthe College of Business at San Jose State University.