Should I stay or should I go? Managing Brazilian Whatsapp

Noname manuscript No.(will be inserted by the editor)

Should I stay or should I go? Managing BrazilianWhatsapp groups

Ana Cristina Bicharra Garcia ·Adriana S. Vivacqua

Submitted: April 20th, 2020

Abstract Instant messaging (IM) technology enables individuals to connect and

maintain relationships with friends, family and colleagues, keeping participants up-

dated on subjects of interest. It has rapidly become widespread in many countries

and even been used for political activism. IM enables rapid, informal interaction

between participants, but can generate message overload and notification fatigue,

which leads to the adoption of different strategies to handle this problem. In this

paper we report on an empirical study focused on the management of IM groups:

reasons for joining or leaving, and the strategies adopted to manage the infor-

mation flow. We distributed a survey that was answered by 442 Whatsapp users

in Brazil. Answers help us understand the ways in which participants cope with

message overload.

Keywords Whatsapp · relationship · communication, social media · design

guidelines · group behavior

Universidade Federal do Estado do Rio de JaneiroAv. Pasteur 458, Urca, BrazilTel.: +5521-2530-8051Fax: +123-45-678910E-mail: [email protected]

Universidade Federal do Rio de JaneiroAv. Athos da Silveira Ramos 274, Cidade UniversitariaTel.: +5521-3938-9515E-mail: [email protected]

2 A.C.B.Garcia, A.S.Vivacqua

1 Introduction

The widespread adoption of mobile technology and instant messaging (IM) systems

have led individuals to adapt the ways in which they communicate with each

other and in groups. Both social networking systems and mobile instant messaging

(MIM) have become highly popular around the world [49], and their adoption has

led to changes in how people communicate with each other and in a group context.

People have come to use MIM for multiple purposes, ranging from staying in

contact with friends to keeping abreast of workplace news [12]. Most of these

systems warn users of incoming messages through notifications, sound-based, vi-

sual or haptic, which translates to a frequent demand for attention that users

have to handle, an unwanted side effect that can lead to anxiety and social media

fatigue [12][15].

One important feature of many IM systems is the ability to create groups

and undertake group discussions. Group messaging are conversations involving

more than two participants [42]. While multiple studies report on IM usage for

individual (one-to-one) communication [5] [8] [22] [31] [47] [48], usage of groups

has not been very explored, with a few exceptions such as work looking at group

coordination [41], daily dwelling [35], group co-presence [27] and activism [36]

[29].

Whatsapp has become one of the most widely adopted mobile instant messag-

ing platforms worldwide [49] [6] [1] , with over 1 billion daily users [14]. In addition,

it is the leading instant messaging platform in Brazil, for multiple reasons [28] [44].

It has become entrenched in day to day life [13] in such a way that any shutdown

might become problematic [40].

This paper reports on a study of Whatsapp users in Brazil, focusing on group

participation. The objectives of our research are to better understand Whatsapp

user behavior in Brazil, as it relates to groups. Our research questions are:

– What variables lead participants to join Brazilian Whatsapp discussion groups?

Managing Brazilian Whatsapp Groups 3

– What variables correlate with determine the co-existence behavior, such as

silencing groups and sharing personal news, of Brazilian Whatsapp users?

– What variables correlate with the exit behavior from discussion groups of

Brazilian Whatsapp users?

To answer our questions, we conducted a survey that was publicly announced

on Brazilian computer science forums. Initially, we interviewed and analyzed What-

sapp group messages of a small group of 7 people, to gain insight for a wider in-

vestigation. We then designed and conducted an online survey, disseminated via

social channels. The survey was open for 10 days and collected over 422 valid

responses. We removed responses 97 incomplete responses. Answers came from

all over the Country (13 different states). We arrived at very interesting findings,

some expected such as the negative impact of age in the number of enrolled dis-

cussion groups and the number of controversial groups and some unexpected such

as the greater likelihood male users will leave when receiving Porn messages than

female users. Our findings are not conclusive since the sample was small, but they

are evidences that open up many interesting questions that deserve further inves-

tigation. People are jumping into Whatsapp discussion groups bringing old social

interaction habits, but adjusting to the new possibilities of relationship.

2 Related Work

Jason Fried, Basecamp CEO, states that the technologies we use also impact on our

well being, and lists the impacts of group chat on organizations. On the positive

side, group chats are good for quickly hashing something out, alerting people that

something has happened, having fun and creating a sense of belonging in a group.

However, it also leads to mental fatigue, a culture of immediacy and fear of missing

out. It also tends to generate instinctive responses, over-messaging and rambling,

among other unwanted behaviors. He wraps up his paper stating that attention is

a valuable resource and that organizations should not use synchronous messaging

as the norm [18].


In a critical paper, Sean Captain [10] refers to studies that point towards group

chats generating better understanding among colleagues, but also reinstates that

group chats tend to generate too many messages and stress workers out. In fact,

a 2015 study points to a significant reduction of stress in a group of people who

checked email only a few times a day (versus those who received notifications upon

arrival) [25].

Birnholtz interviewed 21 former users of instant messaging to elicit their rea-

sons joining, how they adapted as their life changed and what reasons led them

to leave the platform. Among other findings, his study revealed that users tried

to adapt their behavior to handle excessive interruptions, but ultimately the plat-

forms did not support it, so they ended up leaving [7]. The study focused on

individual messaging and not group participation, but the discussion mentions

a need for better ways to manage contacts as a user’s life and context changes.

Quan-Haase and Young [39] also state that social influence is one of the main rea-

sons for Whatsapp adoption. According to them, the nature of Whatsapp tends

to lead to high frequency usage, as it supports social, informal and conversational

communication.

This is in line with [13], who mention that Whatsapp has become an integral

part of life in Mexico, and stress its role in work and family environments, as well

as safety and micromanagement. In these settings, Whatsapp groups have become

an important part of daily life, enabling participants to stay in touch with family

and freinds and get work done. Another study show that users experienced stress

and anxiety, and had to learn to use other tools during a Whatsapp blockage in

Brazil [40]. These further stress the point that Whatsapp has taken a central role

in society in many countries.

Dhir et al.’s research indicates that fear of missing out tended to lead to com-

pulsive media use, which in turn triggered social media fatigue, leading to elevated

anxiety and depression. Social media fatigue is a condition where individuals feel

exhausted after experiencing communication overload through their social media


platforms [15]. Message and notification overload was also illustrated in Hulick’s

paper [21], where he mentions one of the biggest problems in group messaging

is its intrusiveness, and the expectation of constant availability (that one should

always be ready to answer any messages received).

Church and Oliveira [12] conducted research to better understand the adop-

tion and usage of Whatsapp and its relation to SMS systems. Through interviews

and a survey, they established that cost of service and social influence played a

significant role in its adoption. They also found that participants sent significantly

more messages through Whatsapp than through traditional SMS (presumably be-

cause Whatsapp messages are free to send whereas, SMS messages are paid for.)

Participants also state that Whatsapp was more conversational than SMS, which

was seen as more restrictive as senders would try to fit the whole message into a

single message to reduce cost.

In addition, interviews with active Whatsapp users revealed an increased sense

of community and connection. Usage of groups in Whatsapp was very frequent,

driven by the need to organize social events and communicate with small commu-

nities (e.g., family). However, users also pointed out that this usually led to mes-

sage overload (possibly due to ease of communicating). To cope with the system’s

proactive notifications, users would switching phones to silent mode or completely

off [12]. In their data, usage for work correlates negatively with turning the phone

off or setting it to silent mode. More recently, studies have delved into Whatsapp

adoption by activists [29] [36]. Instant messaging groups enable digital activists

mobilize crowds rapidly, and allow conversations to be extended beyond an initial

group, cascading from one to the next through message forwarding.

Smith and Tang [42] state that problems in messaging arise when people use the

same technologies to communicate with people from different contexts. They report

on a study with active group messaging adolescent users (ages ranged from 15 to

24), and use a set of three dimensions to classify groups: Focus, Membership and

Duration. Like other studies before them, they find that participants experience


notification overload, and that their main strategy is to silence the group to avoid

excessive notifications.

Karapanos, Teixeira and Gouveia [23] report on a study regarding the differ-

ences between Facebook and Whatsapp adoption and usage, from a perspective

of need fulfillment. Whatsapp supports more intimate connections better fulfill-

ing their need for relatedness. They report that most unsatisfying experiences on

WhatApp had to do with breaches of offline social norms, such as broadcasting

users’ context. The features that show an individual’s last logon or whether a mes-

sage has been read lead to incorrect assumptions about the person’s context and

to a monitoring behavior. Participants also mentioned the exposure when leaving

a group or being added without approval as potentially leading to unsatisfying

experiences.

3 Research Methodology

Our research was conducted using a survey. Preliminary interviews were conducted

to elicit the main questions that would drive further investigation. We then de-

signed a questionnaire to elicit responses from a wider audience and analyzed the

questionnaire responses. In this section we briefly present survey design followed

by an analysis of the survey data, as it relates to the research questions we posed

earlier.

3.1 Survey Design

Preliminary interviews were conducted with active Whatsapp users of different age,

gender and professional activities, to gain a sense of the typical communication

issues and group membership. Seven people from Rio de Janeiro were interviewed,

recruited via personal connections. The goal of these interviews was to generate

insights into the subject. Interviews were semi-structured and open-ended, and re-

spondents provided a number of examples of their daily usage of group messaging.


We then designed a questionnaire: data for the survey were collected in March

2018 using an online survey tool 1. We advertised the study on several websites of

our Universities and on three official email lists of the Brazilian Computer Society

and also on Facebook and Whatsapp. Participants signed a consent form prior to

responding. The consent form explained the goals of our research and how data

would be used. The consent form also guaranteed the data would be kept confiden-

tial and explained they were free to leave the survey at anytime. The questionnaire

contained 24 questions. Questions were divided into four groups:

– Demographics: questions concerning gender, age, local of residency, education

and professional activity;

– Membership: questions about the number and type of groups they are part of,

reasons for joining or leaving a group;

– Behavioral: questions that concern the frequency with which users read and

post messages, the way they react to inconvenient posts, situations where they

decide to send private messages versus sending them to the entire group, and

how they decide about which group to post messages to;

– Design issues: included open questions to identify functionalities users felt they

needed to better communicate with groups. This was meant as a springboard

for further research.

The online survey was open for 10 days, and elicited a total of 442 responses.

Out of these, 97 responses were discarded because respondents either took less

than 2 minutes to answer or abandoned the questionnaire with less than 50%

completed. As a result, we obtained 325 complete responses (individuals who got

to the end of the questionnaire). The majority of respondents took between 10

and 20 minutes to answer the questionnaire. In this paper we present an analysis

of a subset of the questions.

1 Survey Monkey: www.surveymonkey.com


3.2 Demographics

Survey respondents were evenly distributed gender-wise, with 51% male respon-

dents and 48.7% female respondents (0.3% of respondents chose not to answer

this question.) We also noticed a concentration of highly educated people, which

might be due to the way in which the questionnaire was distributed. About 87.7%

of respondents had at least a College degree. We divided respondents into 5 age

brackets: Post-Millennial (age ≤ 20), Millennial (age 21 to 36), Generation X (age

37 to 52), Babyboomers (age 53 to 71) and Seniors (age ≥ 72 ) [11]. Full demo-

graphic information can be seen in Table 1.

Table 1 Respondents’ Demographic information

Gender Age Range EducationHigh School College Graduate

Female Post Millennial 7Millennial 8 29 17Generation X 3 17 26Babyboomers 4 15 25Seniors 2NA2 5

Total (158) 22 66 70

Male Post Millennial 8 0 0Millennial 9 35 33Generation X 10 30Babyboomers 14 24Seniors 1NA3 1

Total (166) 17 59 89

NA Gender Babyboomers 1

Total (325)

The majority of respondents (71.4%) lived in the state of Rio de Janeiro, which

can be explained by the fact that the questionnaire’s distribution started in this

state. Nevertheless, there were respondents in 12 other states, such as Sao Paulo

(10.7%), Ceara ( 4.7%) and Minas (4.4%). There were also a few respondents in

distant places such as Amazonas, Tocantins, Mato Grosso and Parana, as shown

in Figure 1


Fig. 1 Demographics: Respondent Location

3.3 Group Membership

Every respondent belonged to more than one group. Friendship, family and work

groups account for the entire universe of respondents, i.e, every individual in our

sample belongs to at least one of the these three groups, with over 55% of respon-

dents belonging to all three. The most frequently reported group ties were Friend-

ship (91.8%), Family (83.6%), Work (68.6%), Study (such as courses, contests,

exam preparation) (46.2%), Events (such as organization of birthdays, weddings

or trips) (31.1%) and Leisure (hobbies and sports related) (28.6%), as shown in

Figure 2. Other groups mentioned include sports fan clubs, political groups, reli-

gious groups, people who live in the same building or parents of kids who study at a

given school. The remainder of our analyses correlates the data with participation

in the 6 dominant groups.

Notable in these results is the usage of IM for work/business purposes. Pre-

vious research on IM indicated it was mostly used to keep up with family and


Fig. 2 Respondents’ membership to different types of group. Family, Friends and Work ac-count for all respondents.

friends, planning events and leisure activities [35] [34]. Apparently, between the

time those investigations were conducted and now, IM adoption has grown beyond

the confines of personal messages. Nowadays, it is also being used for work pur-

poses, as can be seen from the fact that over 2/3 of our respondents (68.6%) use

it for work. If we add those up with participants who use IM for study groups, we

go up to 84% of participants using IM for business purposes. More recent work

has investigated the usage of Whatsapp groups for activism. [36] [29] [6]. In the

following sections, we look for patterns on the participants’ entrance, permanence

and exit behaviors.

4 Findings

The step-by-step process of data analysis is shown in Figure 3: we first run a

correlation matrix to check for co-linearity among the independent parameters. If

there is no co-linearity, we can use the LASSO method for selecting the relevant

independent variables. Lasso (least absolute shrinkage and selection operator) [45]


[3] is a linear regression method to predict relations between variables, but here

we used its important sub-product of selecting the relevant variables. With these

variables, we moved on to a logistic regression, which presented better accuracy

than linear models. We run a logistic regression on the set of selected variables,

and the results inspired our hypotheses concerning the variables, for example if age

results in a negative coefficient, we created the hypothesis that the younger the

participant the more active they will be (from simple reading behavior to frequent

posting behavior). Finally we look at pvalues to confirm our hypotheses.

Fig. 3 Data Analysis Process.

4.1 Joining a Group

Our first inquiry is into factors that lead participants to join Brazilian What-

sapp discussion groups? According to our questionnaire, respondents join groups

mainly due to affinity with the theme of the group, as can be seen in Table 2.

Social influence is also present, especially in the case of groups of Friends, but is

surprisingly not the driving element in family and leisure groups. Prior research

had documented social influence as a strong incentive for joining IM platforms [39],

as individuals want to join the platforms where they were most likely to find their

friends. Our findings indicate that, once everyone is using the same platforms,

users feel the need to manage their contacts and message load, and start deciding

which groups to join based on content rather than other participants. Whatsapp

being a predominantly informal means of communication, it makes sense that in-

dividuals would use it to keep in touch with their friends, the one case where social

influence and group theme are balanced (Table 2, column 2).


Table 2 Reasons for joining each type of groups (columns)

Family Friends Work Study Events Leisure

Subject 69% 54% 75% 73% 71% 69%People 31% 46% 25% 27% 29% 31%

One of the respondents left a comment stating that she was included without

asking in most of her groups, which provides an example of social pressure or

expectation to join a group at work. Another respondent mentioned he participated

in 5 hobby-related groups for which he had to apply and wait for acceptance.

We had not anticipated this case, we were expecting to find loosely created and

coordinated groups. These groups have hundreds of participants, are created and

managed by a central administrator who enforces interaction norms. Participants

can be temporarily suspended or even removed form the group. This provided us

with a subject for another study: the dynamics and moderation of large groups in

MIM.

In order to better understand the joining patterns to Whatsapp groups, we

run logistic regression models considering five independent variables:

– Age: an integer value corresponding the age of the participant. It varied from

18 to 84, with an average age of 40 years old. We also subdivided the group

into three generations: Millennial (younger than 40 years old), Generation X

(between 40 and 60 years old) and Baby Boomer (older than 60 years old).

– Gender: Either Male or Female

– Education: Based on the answers, we divided the group into 2 sets: partici-

pants with High School and participants with College degrees. There were 284

participants with a College degree.

– Work: We cluster the answers into three classes: Unemployed or free-lancers

or consulting people; Students, Currently employed people and retired partic-

ipants. There were 147 free-lancers, 59 students, 102 currently employed and

15 retired participants.


Initially, we investigated the correlation between independent variables, and

found that they were weakly correlated. The entrance behavior was reflected by

the number of discussion groups the users were enrolled and the controversial

characteristic of those groups. To investigate that, we considered the following

dependent variables extracted from the participants’ answers:

– Many Groups: a Boolean variable. Participation in up to three groups: family,

friends and work was considered standard. The data corroborates this premise.

Users enrolled in more than these three groups will be classified as True for

the “Many Groups” variable.

– Controversial Groups: this Boolean variable indicates if the user participates

in groups where discussions often lead to a lot of controversy. We distinguish

between formal groups (Work) and informal groups (Family and Friends).

We run the Lasso algorithm [46] to select the relevant independent variables

for creating an explanation model. Table 3 presents the Lasso coefficients of each

independent variable (row values) for each explanation model (column value). As

shown, Age, Place and Work may explain the entrance behavior in many groups.

All five variable may play an important role explaining the users entrance on

controversial groups.

Table 3 Entrance behavior: Lasso coefficients showing the relevant independent variables tocreate an explanation model. “Zero value” means the variable has no importance in explainingthe behavior.

Many Any Controversial ControversialGroups Controversial Group Formal Group Informal Group

Age -0.004665 -0.001561 0.004164 -0.001561Education 0 0.039260 0.037270 0.039260Gender 0 -0.027266 -0.022296 -0.027266Place -0.007897 -0.004975 0 -0.004975Work -0.027569 0.026349 0.043431 0.026349

The Logistic regression fine-tuned our analysis. We reached a model (AUC-

0.66) that depends on Age and Work. As shown in Figure 4, the younger the

person, the more likely they are to join groups other than family, friends and


work. Furthermore, the less formal the work, the more likely the person is enrolled

in more groups.

Fig. 4 Logistic Regression results - Age and Work affects the number of groups a person joins.

We further investigate the conditional probabilities difference when assuming

one of the possible values for the independent variables. For example, we were

interested to know if the probability of enrolling in more groups would be higher

for female participants , i.e., P(ManyGroup—Female) > P(ManyGroup—Male).

As shown in Table 4, people with no formal jobs (shown in the table as Free )

are enrolled in more groups than formally employed people. Female or employed

people tend to be enrolled in more controversial groups at work than male or not

formally employed users. Participants from Rio de Janeiro state are more likely

to be enrolled in informal controversial groups, such as family and friends, than

people that live in other Brazilian states.

As far as enrollment in controversial groups, we could not build any statistically

sound model (AUC≥ 0.6 and pvalue ≤ 0.05) considering the independent variables.

However, we could build an interesting model relating enrollment on controversial


groups and the number of groups a person participate. As shown in Figure 5, the

more groups you are enrolled, the greater the chances to be in controversial groups.

Fig. 5 Logistic Regression results - Number of groups affects the participation in controversialgroups.

Table 4 Entrance behavior: Conditional probabilities considering possible values of the inde-

pendent variables. Values in black means no statistical significance. Pvalues ≤ 0.05 are written

in green. Values in red and green represent the probability of an event given an attribute value

(red shows values ≥ green values)

4.2 Staying in a Group

In our second question, we investigate reasons for staying in a group. Even when

groups slow down and stop messaging, participants tend to stick around: after

becoming a member, respondents tend to continue in the group for as long it

lasts. Table 5 presents some of the main reasons for that behavior. According to

the answers, 49% of the respondents would not leave a family group for fear of

hurting the feelings of other participants and 54% equate leaving a friends group


to loosing contact with participants. As far as business-related groups go, 51%

of respondents would not leave a work group for fear of missing opportunities,

which also holds true for study groups (56%). Staying on top of the subject was a

strong reason to not leave work and study groups, with 40% and 45% of responses

respectively. This was a also a strong reason for staying in events groups, which

is understandable, as these groups are meant for planning and organization, and

usually distribute time-sensitive information. From the data, we notice work and

study groups are handled similarly, and considered spaces where one goes to stay

on top of the latest information and also where opportunities tend to arise.

Table 5 Reasons to stay in a group according to the type of group.


Opportun. 2% 10% 40% 45% 35% 36%Contact 23% 54% 30% 34% 16% 34%Subject 33% 35% 51% 56% 43% 32%Pressure 23% 16% 11% 3% 4% 7%Emotional 49% 33% 6% 5% 5% 8%

This co-existence behavior was reflected by the actions a participant perform

while participating in discussion groups. To investigate that, we considered as

dependent variables:

– Frequency: how often the user checks their messages. We classified participants

as “addicted”, the ones that checks frequently, every 10 minutes up to every

hour. Otherwise, they were classified as “non-addicted” users. We separate the

analysis concerning formal (work) and informal (family and friends) groups:

53% of total users were classified as addicted and 47% as non-addicted users.

– Activity: how active the user is in the group. This may be “active” users as the

ones that read and post at least once a day (38% of users). Otherwise, they were

classified as “non-active” users (62% of users). We also discriminated between

the user’s behavior in formal and informal groups.


– Silence: represents the users’ behavior of configuring groups to silent mode

(26% of users has at least one groups on silent mode). We discriminate between

the behavior in formal and informal groups.

– Sharing news: represents users’ sharing behavior: whether they do not share

good or bad news (8% and 21% respectively), share them with some special

person (66% and 57% respectively) or within a discussion group (13% and 8%

respectively). We discriminate between the behavior in formal and informal

groups.

We run the Lasso algorithms to identify the relevant parameters, as presented

in Table 6.

Table 6 Co-existence behavior: Lasso coefficients showing the relevant independent variablesto create an explanation model. Freq means frequency; Generat means Generation; Educ meansEducation; Good means sharing good news; Bad means sharing bad news; FF means Familyand Friends

Age Generat Educ Gender Place Work

Active-Any 0 0.0435 -0.0298 -0.0812 -0.01797 -0.0448Active-Work 0.0012 0 0.0858 0.01147 -0.0074 -0.0626Active-FF 0 0.0435 -0.0298 -0.0812 -0.01797 -0.0448

Freq-Work 0 0 -0.0394 0 -0.0117 -0.0058Freq-FF 0 0 0.0459 0 0 -0.0792

Silent-ALL 0 -0.0269 0.1568 0 0 0Silent-Work 0 0 0.1219 0 0 0Silent-FF 0 -0.0687 0.1273 0.0213 0 0.0108

GoodBadNone 0 0 0 0.0272 0 0GoodNone 0 0 0 0.0355 0 0BadNone 0 0 0 3.70E-17 0 0GoodBadOne -0.0039 0 0 -0.1553 0 0GoodOne -0.0065 -0.012 0.0260 -0.1482 0 0BadOne -0.0036 0 0 -0.1475 0 0.0037GoodNewsGroup 0.0035 0 0 0 -0.0073 0.0133BadNewsGroup 0 0 0 0 -2.4E-18 0GoodBadGroup 0.0009 0 0 0 0 0

We further analyzed the data and calculated the conditional probabilities for

the different possible values of the independent variables. As shown in Table 7,

our data indicates that older people and female are more active on groups (mainly

posting) than young or male users. College and female users are more frequent on


discussion groups than high school and male users. Users without a formal job are

more frequent on work-related groups. College and formally employed people are

more likely to silence groups than high school or not formally employed users.

Table 7 Co-existence behavior: being Active and Frequent in groups, Silencing groups andSharing good or bad news with groups. Values in black means no statistical significance.Pvalues ≤ 0.05 are written in green. Values in red and green represent the probability of anevent given an attribute value (red showns values ≥ green values

4.3 Managing Messages

At the end of our survey, we added a question regarding missing Whatsapp func-

tionalities and design, to collect evidence for further research. This question was

optional and received few responses with new information. This was a single ques-

tion with six pre-existing options (no new knowledge related to them) and an

”Other” option for actually sourcing creative answers. The existing options were

there to create a context. Possible answers consisted of:

– Silencing individuals within a group

– Blocking messages from certain individuals (automatically delete these mes-

sages, as if they were spam)

– Blocking messages based on characteristics such as content, length, audio or

video

– Classifying messages


– Organizing messages

– Prioritizing messages

Respondents selected options as needed, and included new elements. The open

answers indicate participants don’t want people, within a group, to notice their

actions of silencing individuals or contents. This also exposes a need for privacy,

since Whatsapp informs the group when someone leaves. The most interesting

responses are mentioned below:

– Find a message you don’t remember in which group you read it (search)

– Leave the group without being noticed (privacy)

– Filter repetitive messages (filter)

– Prioritize messages by sender (prioritize)

– Store in a place you could retrieve later (retrieval)

– Configure posts’ filters (filter)

– Get to know what is going on without reading all discussion so far (summarize)

– Mark important messages for later review (tagging, organization, retrieval)

– Prioritize groups (prioritize)

– Organize messages per sender even among groups (organization)

– Offer a reputation system based on ”likes” on posts (people would give likes

in posts) (reputation)

– Offer an anti-spoiler functionality, so people would only be able to read the

message when clicking on it (previews)

These responses reinforce the need for better organization techniques. This is

directly related to information overload: users have so many messages and contacts

they now need ways to filter undesired ones, block unwanted content, and better

manage messages they receive. Email went through a similar cycle, and the number

of emails became so large that organizational mechanisms were needed to handle

message influx (i.e., labels, rules, searches, priorities, etc.) These results indicate

respondents would like to have more control over their communication and be able

to organize messages and recipients, and we will conduct further investigation into


this problem and experiment with designs/solutions to help users manage message

overload.

4.4 Leaving Groups

Our last question regarded situations that would cause individuals to leave a group.

Personal offenses or threats were mentioned as the main reason for leaving a group

across the board (see Table 8). Offenses accounted for leaving non-familial groups

in over 60% of responses and threats accounted for more than 50%, except in the

case of family and friends groups. Also worthy of notice, comments that go against

one’s personal ethics or beliefs were cited as a strong reason to leave a group. Porn

appears as a reason to leave Work, Study and Events groups.

Table 8 Reasons to leave a group according to the type of group.


Porn 35% 31% 44% 46% 48% 37%Long Msg 29% 27% 26% 27% 35% 35%Conflict 32% 33% 27% 27% 25% 29%Ideas 12% 13% 12% 16% 20% 23%Ethics 32% 42% 39% 42% 47% 49%Threats 35% 48% 55% 58% 52% 54%Greetings 23% 17% 23% 21% 31% 27%Offenses 57% 65% 64% 65% 68% 67%

The exit behavior was reflected by the scenario that would justify a partici-

pant leaving a discussion group. To investigate that, we considered the following

dependent variables:

– No way out: a Boolean classification that represents a user’s inability to leave

a group (either due to emotional or opportunistic reasons). We analyzed sep-

arately behavior in formal (work related) with informal (family and friends)

groups.

– Exit - Porn: we investigate the user’s propensity to leave a group when receiving

porn related messages.


– Exit - Conflicts: We investigate a user’s tolerance (and propensity to leave) to

heavy conflicts among participants, that may include himself/herself, and that

may include personal offenses.

– Exit - Msg: We investigate a user’s intention to leave a group due to a over-

whelming number of messages, i.e., whenever the messages become too long or

empty in content (too many salutations).

As shown in Table 9, Education plays an important role for explaining any of

the exit behaviors.

Table 9 Exit behavior: Lasso coefficients showing the relevant independent variables to cre-ate an explanation model. Co-existence behavior: Lasso coefficients showing the relevant in-dependent variables to create an explanation model. Generat means Generation; Educ meansEducation; Msg means too long messages or too many salutations

Age Generat Educ Gender Place Work

No-Way-Out-ALL 0 -0.0131 0.0048 0 0 0No-Way-Out-Work 0 -0.0396 0.3029 0 -0.0108 0No-Way-Out-FF 0 0 0 0 -9.6E-18 0

Exit-Porn 0.0001 0.0355 0.0408 -0.0642 -0.0121 0Exit-Msg 0 0 0.0842 0 0 0Exit-Conflict 0 0 0.1971 0 -0.0057 -0.0023

We also analyzed the behavior comparing the possible values for each of the

independent variables. As shown in Table 10, participants are more likely to re-

main in discussion groups of family or friends than work-related. They also are

more likely to leave a discussion group due to conflicts than any other reason.

Formally employed or college-level users are more likely to stay longer in work-

related discussion groups (despite wanting to leave) than informally employed or

high school-level users. Older people are more likely to remain in informal groups

(family and friends) than younger people. Formally employed or those holding a

college degree are more likely to leave groups due to either Porn, Conflicts or Long

messages than those informally employed or holding a high school degree.


Table 10 Exit behavior: reasons for leaving or unwillingly staying in discussion groups.

5 Discussion

Our studies ratified the idea that most people are suffering from the Fear of Missing

Out (FOMO) syndrome [38]. They engaged in many discussion groups possibly as

a reaction of being socially excluded from the group [38]. As our study has shown,

they stayed connected, mostly, not to miss opportunities in either groups related

to the work or more informal groups as family and friends. Since Whatsapp is

a smartphone app, groups become omnipresent. As Elhai, Lenine & Dvorak [17]

argue, people have become addicted to smartphone interaction. Sometimes, people

might even ignore a companion to remain connected to the smartphone interaction

(phubbing) [4]. FOMO can explain enrolling in many groups and staying in the

groups despite wanting to leave. Nevertheless, it remains an open issue to under-

stand the reasons that justify people not silencing groups. Would it be for FOMO?

Maybe the reason lays on another problem concerning digital literacy. We could

not find patterns relating to age, gender or education. However, we are wondering

if this behavior was for technology illiteracy or semi-illiteracy. People got into IM

without any training and keep learning by doing. There are some studies [40] [24]

discussing the impact of digital literacy and how a user can remain in an island of

knowledge. Consequently, a possible hypothesis is that people did not silent their

groups for not knowing the functionally. This deserve a further study.

An unexpected finding was related to the exit behavior in case of receiving

porn messages. We were expecting a stronger reaction from women, but it was not

confirmed by our data, especially on work-related discussion groups. According to

Attwood [2], porn messages create a environment in which women are viewed as


objects, and may even be considered a type of implicit sexual harassment. There

might be a cultural issue here that also deserves further research.

Additional questions explored participants’ behavior. According to our survey,

more than 50% of respondents set all of their groups to Silent mode, reading posts

on demand a few times a day, as illustrated in Figure 6. By setting groups to silent,

users avoid excessive notifications and handle incoming messages periodically.

Fig. 6 Frequency with which respondents check messages according to type of group.

In comparison to other types of groups, work-related groups are less frequently

set to silent, presumably because members feel they need to stay informed of what

is going on. As can be seen in Figure 7, the most important reason for setting

a group to silent is not wanting to be disturbed all the time, followed closely by

groups being too “noisy”. This is an indication of social media fatigue, which has

also been reported elsewhere [19] [16] [51]. As groups gain size and traction, the

number of messages increases and so does the number of notifications. Silencing a

group or the whole phone is a reaction and a way to deal with notification over-

load. Interestingly, work and study groups were the ones considered least “noisy”


(possibly more focused on the themes with fewer off-topic/random posts), and

were sometimes set to silent because respondents habitually set all their groups to

silent mode. Curiously, some respondents said they weren’t sure why they set their

groups to silent. We assume these are respondents who habitually silence all their

groups (or even the whole phone), so they don’t even consciously think about it.

Fig. 7 Reasons to set groups to silent mode according to type of group.

For all groups, most respondents said they read frequently but rarely post

(Figure 8). This lurking strategy is very common in social media [32], and also in

communities of practice, which are usually made up of a core group of participants

and a much larger set of peripheral members [50] [37] [26] [43]. Table 11 shows our

findings regarding silencing certain groups.

Table 11 Groups on silent mode


Silence 59% 57% 51% 56% 67% 69%Mode


Fig. 8 Read and post behavior in Whatsapp

More than 50% of respondents choose to ignore inconvenient or long messages

in every group, as seen in Tables 12 and 13. For about 30% of respondents,

long posts might draw some attention, depending on who is the sender of the

message (Depend on Sender in the table). When respondents decide to complain

about inconvenient posts, they do so publicly (Table 12, row Complain Publicly)

rather than privately (Table 12, row Complain Privately), and this happens more

frequently in work or study groups. These groups should be more focused, so

complaining publicly is a reasonable choice, as it steers the group back to focus and

reinstates the group’s purpose and/or norms for all participants at the same time.

One interesting note can be made about long messages: because Whatsapp is an

IM system, and these were originally inspired on SMS (Short Message Service) [12],

there is an implicit expectation that messages will be kept short and direct [9].

Typing lengthy messages is certainly not easy on a smartphone, but Whatsapp is

also accessible via a Web interface, which makes it a lot easier to compose and

post long messages.


Table 12 Participants’ reaction to inconvenient messages that don’t conform with theirmoral/ethical code

Reason: Against moral/ethical code


Depend on sender 24% 23% 17% 16% 17% 18%Read the message 22% 25% 21% 27% 19% 25%Forward the message 29% 34% 22% 24% 14% 25%Delete the message 17% 18% 18% 15% 13% 13%Ignore the message 47% 47% 54% 54% 49% 53%Complain publicly 15% 16% 19% 18% 12% 18%Complain privately 13% 13% 15% 10% 11% 12%Leave the group 10% 11% 11% 12% 27% 16%

Table 13 Participants’ reaction to long messages or video/audio

Reason: Long or Audio/video


Depend on sender 37% 35% 31% 27% 31% 33%Read the message 23% 29% 28% 33% 27% 32%Delete the message 24% 23% 22% 21% 16% 18%Ignore the message 65% 59% 60% 62% 58% 60%Complain Publicly 5% 4% 5% 3% 3% 0%Complain Privately 3% 1% 2% 3% 3% 3%Leave the group 0% 0% 1% 1% 4% 1%

In an open question, we investigated functionalities users would like to have.

The ability to silence individuals within groups was the top mention, followed by

organizational functionalities, such as classifying messages, searching for messages

(in multiple groups), prioritizing certain users, blocking certain content and being

able to leave the group without being noticed. These indicate users don’t want

people, within a group, to notice their actions of silencing/filtering individuals

or contents. They also expose a need for better privacy control and organization

techniques. A side effect of the way in which Whatsapp exposes members leaving

or joining groups is that participants might feel embarrassed to leave a group

because others will see and question their decision. Thus, they will often stay and

silence the group rather than leave, or let people now they are leaving providing

justification for doing so. Social pressure plays a part in the decision to leave a

group. These initial results will lead into further investigation.


6 Conclusions and Future Work

This paper presented an exploratory survey study with Whatsapp users. The pur-

pose was to understand the interaction dynamics within groups in IM, and how

individuals handle message and notification overload. Whatsapp is the most pop-

ular communication media in Brazil, one that enables people to stay connected

on a daily basis. Our study sheds light on interaction issues of MIM groups and

raises design issues to be addressed in future design systems.

The study indicates that people join groups due to affinity either with the sub-

ject or with the people, and they stay in the group until it dissolves, but often set

it to silent so they won’t be disturbed by notifications. This seems easier than leav-

ing a group, as leaving is a public action that sometimes has repercussions (such

as getting excluded, receiving additional messages and starting a new discussion.)

Our study with Whatsapp users reinforces the observation that lurkers are the

dominant population in communication media [32], [33]. They read frequently,

but rarely post messages. To reduce overload, participants end up setting groups

to Silent, and checking messages periodically, a few times a day. This is curious,

as it takes the “instant” out of “instant messaging”: what was meant to be a syn-

chronous communication means becomes asynchronous because participants can’t

handle the message/interruption overload. This points to other lines of inquiry,

such as how to manage message and notification overload, and determining when

it sets in.

Groups are open spaces in which members are considered to have the same

degree of intimacy so any news will be equally shared with all. The indiscrimi-

nate addition of new members may lead to weakening of the ties between some

participants and the group as a whole. New communication media have changed

the way people communicate with groups and with each other [13] [40]. Aristotle

observed that “Man is by nature a political animal” [20] [30], and that is reflected

in participants attitudes towards IM groups to a certain extent. Most Whatsapp


users avoid posting messages that might create conflict in heterogeneous groups

and try to avoid embarrassment or break personal ties.

Our findings point to a need for better organization techniques. They are di-

rectly related to information overload: users have so many messages and contacts

they now need better ways to manage these.

Our study is limited to small and medium sized group interaction of Brazilian

users using Whatsapp for IM. This implies three limitations: cultural, group size

and diverse instant messaging tools. Even though the study consisted only of

Brazilian participants, we believe some findings may be relevant beyond Brazilian

borders. Future work includes studying cross-cultural comparisons including other

countries that favor Whatsapp as their IM communication system. We would also

like to investigate if our findings persist in other IM systems (e.g., Telegram), and

establish requirements for designing MIM systems that address the complaints

noticed by the respondents in our study. We believe large groups with hundreds

of people may present different interaction dynamics that deserve a specific study,

specifically concerning the spread of Fake News. By further interacting with our

respondents that participate in larger groups, we can start looking at the dynamics

of large group interaction in MIM.

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Documents

Should I stay or should I go? Managing Brazilian Whatsapp