Consideration in Software-mediated Social Interaction

Raian Ali, Nan Jiang, Sherry Jeary, Keith Phalp

Outline

Problem Aim Method Results Challenges Conclusions

Problem

Being considerate is important in any business environment but sometimes it is down to personal choice.

People are trying to be considerate in “traditional” communications but not always in software mediated communications This often leads to negative impacts

Examples

Seeing more and more people being copied in an email conversation Being cc’ed without specifying why and

what exactly to look at

Being forwarded an email with FYI without specifying why and what exactly to look at Other short emails with only a few words or no

word

Research Aim

Understand how users perceive consideration in software-mediated interaction to improve social interaction facilitated by software Our ultimate goal is to develop

considerate software

Method

Mixed methods research Sequential exploratory designs (Stoller

et al, 2009)

Phase 1: qualitative research Exploration

Phase 2: quantitative research Validation and elaboration

Qualitative Phase

Semi-structured interviews

Participants: 8 professionals (6 males and 2 females)

with multicultural background living and working in the UK

Different roles from office worker to senior management

Age: 35 (Median), 37.5 (Mean)

Interview Questions

General Cognitive understanding, motivations for being

considerate/inconsiderate Popular software means used in workplace

Specific (software-mediated) Consideration/inconsideration User’s attitude and reactions Decision shift of being considerately or

inconsiderately treated Expectations of software on consideration-support

Quantitative Phase

Large scale online survey

Questionnaire based on interview findings

Distribution channels (UK and US): BU academic staff mailing list Chinwag mailing list Several research mailing lists

Respondents: 122 (67 males, 55 females)

Age Distribution (Survey)

0%20%40%

18-24 25-34 35-44 45-54 55-64 65-74

Age Groups

Perc

enta

ge

Results Overview

Overall user perception mapped well Over 90% agreed, only 9 new codes proposed from less

than 10% respondents

Gender effects are not significant in all areas Cross tabulation, Chi-Square p> 0.05

Age effects are significant in some areas Cross tabulation, Chi-Square p> 0.05

Perception of consideration/inconsideration has impact on specifying consideration

Goal of Interaction

Goal of the interaction itself [65%]: “If they are not interacting for the right reason, then I am

less likely to be considerate”.

Constraints on achieving the goal [59%]: “In my reminders, I could be inconsiderate because of the

urgency and importance of attending the event, nothing personalised”.

Availability of other methods to achieve the same goal [56%]:

“Some people were in the habit of opening the shared file and then wandering off. They lock it. They could work-offline and then upload all text together”.

Consequence

Consequence on the organisation [63%] “Consideration needs managing otherwise destroys projects”

Colleagues’ reactions [59%] “I would deal with senior managers and close colleagues

differently”

Mental cost [55%] “If I did inconsiderate interactions, it makes me feel bad”

Social isolation [22%] “I want to be a nice person because I need to work with

them every day.”

Audience

Relation with the audience [76%]

Value of the audience [54%]

Personality of the audience [74%]

Interaction history with the audience [79%]

Situation awareness [63%]

Visibility of the interaction to other audience [56%]

Types of Inconsideration

Membership termination [59%] Locking [49%] Ignoring [70%] Flame wars [50%] Laziness/Carelessness [61%] Formality level [19%] Timeliness [60%] Pressure [49%] Invading personal space [50%] Irrelevance [36%] Violation of the norms [31%] Curt/ Abrupt wording [61%]

Treating Inconsideration

Behave in an ad-hoc way [25%] Conservative [37%] Receptive [48%] Anxious [35%] Practical [32%] Authority seeker [17%] Evasive [14%] Apologetic [36%]

Age Effects on Reaction

18 – 24 yrs old were more passive “I prefer others to handle this”

25 – 34 yrs old were more proactive “I will report it” “I will say it to the other”

35+ yrs old showed less interests, tend to ignore “Let it be”, “let’s just focus on the business”

Visibility

Explicitly said [40%]

Anonymously said [24%]

Said by an authority [28%]

Learned over time [59%]

Perception Impacts: Consequences

“I didn’t realise it could be inconsiderate for someone” People were more concerned about

their own mental cost (60% agreed)

“It could be inconsiderate” People were more concerned about

their recipients’ reactions (71.88% agreed)

Perception Impacts: Attitudes

TIL – “Today I learned” 59.68% would prefer that others learn

their view of consideration/inconsideration over time through the way they interact with them

“The big brother is watching you” 62.07% - 79.31% respondents would like

“third-party” to get involved as this will not affect their relationships

Perception Impacts: Reactions

“I am cautious to my own behaviour so I will be cautious to others behaviour” 73.5% respondents would be cautious what

they do Less than half of them would feel bad if

they did something inconsiderate

“Fair play” 58.82% don’t mind if they would be treated

in the same way as they treated others

Challenges

Users as modellers: only user can model themselves

Tacitness: easy to feel but difficult to elicit

Personal vs. public: private but can be leaked

Evolution of perception: change over time

Context-dependency: goal driven

Measurement: how it can be measured for each individual

Learning and adaptability: software needs to learn and adapt according to user actions/behaviours

Conclusions

Empirical study to deduce a number of observations on the nature of consideration

A starting point for understanding how to move towards building considerate software

Models and tools will be developed to capture user concerns in software mediated communications