From Digital Footprints to Facts: Mining Marketing Policies of the

Greek Community on Instagram and Youtube

Dimitris Linarakis, Stefanos Vlachos and Paraskevi Raftopoulou

Dept. of Informatics and Telecommunications, Univ. of the Peloponnese, Greece

Keywords:

Social Media, Big Data, Data Analysis, Data Mining, Inﬂuencer Marketing, Covid-19, Greek Community,

Instagram, YouTube, Web Scraping, NoSQL.

Abstract:

Social media have conquered the widest spectrum of our lives. Companies, following the phenomena of the

new digital era, are giving up traditional practices and use new policies of diffusion for advertising products

and for engaging potential customers. In the context of ENIRISST+ (https://enirisst-plus.gr), we started in-

vestigating whether transportation businesses (i.e., ferry companies, airlines, etc.) use the new era practices

for promoting their products and services and then, extended our research on all kind of businesses. The

work presented in this paper studies this shift for the Greek Instagram and YouTube community, records and

analyses the activity of prominent Greek companies on social media, and measures the social and commercial

impact of the emerging COVID-19 pandemic during 2020 on Greek users’ digital behaviour. Subsequently,

we use the acquired data and analysis (i) to draw conclusions about the digital behaviour and preferences of

the Greek social media scene and (ii) to compare the results in marketing policies and behavioural patterns on

two inherently different social media platforms. This is the ﬁrst study in the literature to perform an analysis

on the behaviour of the Greek community in different social media.

1 INTRODUCTION

The last twenty years, with the evolvement of digital

services and the explosion of social networks, many

aspects of our lives as well as our way of thinking

and acting have been radically affected. Social net-

works hold a central role in interpersonal relation-

ships, in the dissemination of information, knowledge

and technology, in the formation of trends, and in

the adoption of opinions; an ever-increasing number

of users engages with and is affected by a multitude

of posts on Instagram, YouTube, or Twitter (Eirinaki

et al., 2018; Peng et al., 2018). This phenomenon,

along with the fact that most content on online so-

cial networks is user-generated, has prompted many

businesses, not only to have digital presence on social

media, but also to give up the traditional advertising

practices and use new policies, ﬁtting the customers’

engagement with the social platforms, for promoting

their products and services.

Among the various modern marketing techniques

stands inﬂuencer marketing (IM). IM is a process

of diffusion over social networks (Wang and Street,

2018), according to which a company, that wants to

market a product or service cost- and time-effectively,

identiﬁes a small number of users (inﬂuencers) with

high social network impact and whose social network

presence tallies with their products. These users are

becoming the initial adopters of the product recom-

mending it to their friends (followers), expecting that

their friends will be inﬂuenced to purchase the prod-

uct and in turn, inﬂuence their own friends, causing an

inﬂuence dissemination (through the social network)

and eventually the wide adoption of the product. A

recent survey (Advertising, 2019) shows that 80% of

the consumers made purchases recommended by in-

ﬂuencers. The work in (Vrontis et al., 2021) is a

systematic review that identiﬁes the key themes and

the dominant concepts of social media IM. Moreover,

(Chen et al., 2021) shows that platform characteristics

signiﬁcantly affect consumers’ purchase behaviour.

Instagram is the most used platform in the fash-

ion industry. A large number of studies (Boerman

and M

uller, 2021; Casal

o et al., 2020; Djafarova and

Rushworth, 2017; Lin et al., 2019; Djafarova and

Bowes, 2021; Asdecker et al., 2021) address inﬂuence

dissemination and marketing under different perspec-

tives attempting to gain insights on Instagram market-

ing tools, on the inﬂuencers’ personalities and on the

consequences of IM on the purchase behaviour. The

Linarakis, D., Vlachos, S. and Raftopoulou, P.

From Digital Footprints to Facts: Mining Marketing Policies of the Greek Community on Instagram and Youtube.

DOI: 10.5220/0011138600003269

In Proceedings of the 11th International Conference on Data Science, Technology and Applications (DATA 2022), pages 219-226

ISBN: 978-989-758-583-8; ISSN: 2184-285X

219

last couple of years, the YouTube platform has also

evolved as a primary marketing selection for brands

promotion. Related works (Xiao et al., 2018; Acikgoz

and Burnaz, 2021; Schwemmer and Ziewiecki, 2018;

Prasad, 2018; Carreon, 2019; Boerman and van Rei-

jmersdal, 2020; Coates et al., 2020) study the role of

YouTube as a social media platform and its impact on

creating visibility on brands, as well as how cues in-

ﬂuence credibility evaluations of posted information.

In this context, we started our research by inves-

tigating whether transportation businesses (i.e., ferry

companies, airlines, etc.) use the new era practicies

for promoting their products and services; there was

not a relative study available so far. We then gen-

eralised our research on all kind of businesses, fo-

cussing though on Greek market as it has recently

entered social platforms. In this work, we study and

analyse the interplay of commerce with popular social

media platforms discerning three fundamental axes:

(i) the common users’ digital behaviour, (ii) the inﬂu-

encers’ digital behaviour, and (iii) the interest of com-

panies to draw marketing policies grounded on these

behaviours. Based on their popularity during the year

2020, their different characteristics, and the continu-

ously increasing commercial interest for them, we se-

lected Instagram and YouTube platforms as the main

subjects of our study.

Our research process is unfolded in two stages: (i)

data collection and storage and (ii) data analysis. At

the ﬁrst stage, two web spiders were developed, us-

ing the Scrapy framework,

one for each platform;

the spiders received as input an initial hand picked

list of users and collected data from Instagram and

YouTube. Consequently, the collected data was stored

in a mongoDB

NoSQL database. Due to the fact

that some ﬁelds of interest were not available for re-

trieving, we prepared and gave out to a wide range (in

terms of characteristics) of volunteers a questionnaire

in order to enrich the scraped data. Then, we anal-

ysed, based on the qualitative and quantitative prop-

erties of the data, the activity of the Greek market.

The contributions of our work are as follows: (i)

we present a qualitative analysis of the activity of

the Greek community on social platforms; to the best

of our knowledge, this is the ﬁrst study concerning

the behaviour of the Greek community on social net-

works, (ii) we identify the marketing policies and be-

havioural patterns in Instagram and Youtube, (iii) we

compare the results of these two completely different,

in terms of content and interaction, social platforms,

and (iv) we examine the social and commercial im-

pact of COVID-19 on social media users’ activity.

https://scrapy.org

https://www.mongodb.com

This work is the ﬁrst step to build a general frame-

work to collect and analyse data from social platforms

with minimum user intervention and by using ﬁlters

per country, per topic, and/or per social network.

In the rest of the paper, we discuss the data col-

lection and storage in Section 2, followed by the data

analysis process in Section 3 and the results of our re-

search in Section 4. Finally, Section 5 concludes the

paper and gives future directions.

2 DATA COLLECTION &

STORAGE

We searched for Greek non-private accounts, which

had uploaded content within 2020 and maintained

at least 1K followers (resp. 5K subscribers) on In-

stagram (resp. YouTube).

These guidelines were

set based on the fact that non-private accounts house

publicly accessible data and also, have the poten-

tial to monetise their posts by promoting or selling

a product or service (Dreghorn, 2020). We devel-

opped automated software that extracted the creden-

tials of popular Greek content creators from credi-

ble web sources. For scraping the initial accounts

sample we used starngage,

a marketplace that con-

nects brands with content creators from different me-

dia, and stats.videos,

which includes YouTube statis-

tics for popular video creators per region. Moreover,

we collected the names of Greek businesses having

digital presence in social media from socialbakers,

a site that includes social media insights per indus-

try or region. Eventually, we collected 2,766 Greek

Instagram proﬁles (784 Male, 926 Female, 806 Busi-

ness, and 249 Other) and 2,068 Greek YouTube chan-

nels (782 Male, 318 Female, 314 Business, and 654

Other), which will be later used as the feed sample

of our scraping algorithms. The set of uncategorised

(Other) accounts consists of proﬁles that are not ad-

ministrated by individuals and includes impersonal

accounts, i.e. proﬁles administrated by groups of peo-

ple (e.g., tv channels, magazines, etc.).

[Instagram Dataset]. An Instagram (IG) account

consists of 10 attributes, including Username, Num-

ber of followers, etc. Also, IG provides the capabil-

ity of uploading a variety of content types, including

24-hours posts (i.e., IG stories) and posts that remain

The thresholds do not hold for business accounts.

https://starngage.com/app/global

https://stats.video/top/most-subscribed/

youtube-channels/greece/of-all-time

https://www.socialbakers.com/statistics/youtube/

channels/greece

DATA 2022 - 11th International Conference on Data Science, Technology and Applications

220

visible on the user’s feed until deleted. Despite the

fact that numerous techniques were available for col-

lecting the above mentioned IG ﬁelds, the complex-

ity of using an authorised IG API led to the use of

our software. An automated web scraping mecha-

nism was developed, using the Scrapy framework and

the Python programming language, which follows the

given steps: (1) Access to the usernames of IG ac-

counts that were initially collected. (2) Generate the

URLs and the request for the source code of each ac-

count. (3) Extract the JSON structure from the HTML

source code of each account. (4) Extract the personal

information related to each scrapped account from the

JSON structure. (5) Access to the ﬁrst 12 posts of

each account and collect their information; IG groups

the posts of each account in subsets of 12. (6) Request

for the next 12 posts of each account and collect their

information. (7) Repeat Step 6 until all posts of the

account have been scraped. (8) Group the data re-

lated to each account in data sets and store this in the

database.

[YouTube Dataset]. A YouTube (YT) channel con-

sists of 8 attributes, including Username, Number of

subscribers, etc. In contrast to IG, the YT platform

provides the YT Data API, which supports the in-

teraction of developers with a wide variety of infor-

mation related to YT creators and content, enriching

also the retrieved data with the adittiobal ﬁelds (e.g.,

Channel/Video ID, or Channel/Video keywords), al-

lowing us to have access to hard-to-reach data. The

communication with the YT Data API was estab-

lished via an automated mechanism that was devel-

oped using the Scrapy framework. In order to retrieve

data from the API, an appropriate HTTP request was

needed, so that the requested data is speciﬁed. The

successive steps are as follows: (1) Access to the

channel IDs of YT channels that were initially col-

lected. (2) Generate a URL that requests from the API

the set of general information about each channel. (3)

Collect the desirable ﬁelds (4) Generate a URL that

requests from the API the ﬁrst subset of videos for

each channel; YT Data API groups the videos of each

channel in subsets of 50, which are interconnected us-

ing pointers. (5) Generate a URL that requests from

the API information related to the scraped videos. (6)

Collect the desirable ﬁelds. (7) Repeat Steps 3-5 until

all the videos of each channel have been collected. (8)

Group the data related to each account in datasets and

store it in the database.

The code of our scraping mechanisms is available

on GitHub.

7,8

[Questionnaire]. The privacy policies of the IG and

https://github.com/DimitrisLinarakis/

https://github.com/stefanos-vlachos

YT platforms, in addition to the relatively limited

amount of information available for collection, pre-

vented our access to ﬁelds, which could enrich and

confer completeness on the ﬁnal conclusions of the

present study. It was thus, decided to create and dis-

tribute a questionnaire, using Google Forms, in order

to both provide a deeper insight of the preferences of

Greek social media users, compared to the more im-

personal metrics that had already been collected, and

help in assessing the effectiveness of the diverse pro-

motion techniques on social media, such as the use of

hashtags, the cooperation with other content creators

or the paid promotion of content.

Our questionnaire aimed at different Greek users

of IG and YT, in terms of age and social character-

istics. In particular, the questionnaire consisted of

4 introductory questions, 23 questions related to IG

and 20 questions related to YT. The questionnaire

was answered by 270 people above the age of 18,

including 187 women (69,3%), 82 men (30,4%) and

1 non-binary person, whilst 128 of the participants

(47,4%) were from the 18-24 age group, 53 (19,6%)

from the 25-34 age group, 66 (24,4%) from the 35-44

age group, 20 (7,4%) from the 45-54 age group and 3

(1,1%) were above the age of 55.

3 ANALYSIS PROCESS

IM is an emerging ﬁeld and the research questions we

are challenged to answer are the following.

• Which are the underlying factors that drive users

of networking platforms to interact, at an ever-

increasing rate, with the content of the platform

at a daily basis?

• Which were the preferences of the Greek social

media community during 2020? Are these prefer-

ences age or gender related?

• Which were the thematic categories and types of

content that obtained signiﬁcant attention by the

users during 2020? Which of these categories

strived in 2020, in terms of content production?

• What is the role of businesses in social media

and which are the potential relationships devel-

oped between the various categories of content

creators?

The breakout of COVID-19 during 2020 brought rad-

ical changes to people’s daily lives, prompting us also

to examine the exact effects of COVID-19 on the

Greek social media community.

[Raw Analysis Measures]. We are interested in ad-

dressing the factors that affect the performance of an

From Digital Footprints to Facts: Mining Marketing Policies of the Greek Community on Instagram and Youtube

221

uploaded post, and, thus, the rate of the exerted in-

ﬂuence. Primarily, the popularity of an account can

be inferred from the number of followers/subscribers

that this account maintains. Accordingly, the number

of “Like” reactions on IG/YT uploads can provide a

ﬁrst insight of content dynamics. On the contrary, the

number of “Dislike” reactions on YT videos can sig-

nify the negative inﬂuence of content on the audience.

The number of views on IG and YT videos can be also

considered as a popularity indicator. All these form

the basic axis on which the content creators’ inﬂuence

is measured and collated with the IG/YT ﬁelds we

can detect potential correlations that further signify

the inﬂuence rate of a creator. Finally, the question-

naire serves the need for an ancillary research tool for

data collection, as follows: (i) Verify the already col-

lected data, (ii) Address the reasons why users follow

inﬂuencers, (iii) Assess the inﬂuence rate of funded

promotions, (iv) Examine the relationship between

the popularity of an account and its inﬂuence rate,

(v) Capture the community’s preference on IG stories

over feed posts, and vice versa, and (vi) Collate all the

collected data with social media users’ gender (Male,

Female, Non-Binary) and age (18-24, 25-34, 35-44,

45-54, 55+).

[Performance Metrics]. We trace more complex cor-

relations and enhance the accuracy of the primary ob-

servations, in terms of the inﬂuence rate and the map-

ping of the social and commercial relationships devel-

oped on social media (Sehl and Tien, 2020), by using

the following metrics. For the IG data: (i) Engage-

ment Rate Post measures the performance of a post

and is calculated as (Post Likes / Account Follow-

ers) × 100, (ii) Engagement Rate Comments Post pro-

vides a deeper insight into the performance of a post

and is calculated as [(Post Likes + Post Comments)

/ Account Followers] × 100, (iii) Engagement Rate

Views measures the performance of a video and is cal-

culated as (Video Likes/Video Views) × 100, and (iv)

Average Days Between Posts reﬂects the average up-

load frequency of a content creator and is calculated

as Sum of days between successive posts/(Total 2020

Posts - 1). Accordingly, for the YT data: (i) Video

Dislikes Ratio reﬂects the negative impact of a video

on the community and is calculated as Video Dis-

likes/(Video Likes + Video Dislikes), (ii) Video En-

gagement calculates the engagement of the commu-

nity with a video and is given as (Video Likes + Video

Comments)/Video Views, (iii) Views Subscribers Ra-

tio measures the average percentage of the subscribers

of a channel that watch the uploaded videos and is cal-

culated as Video Views.

[Outliers Management]. During the analysis stage

of the data, there were accounts and posts that gath-

Figure 1: Avg engagement per account category (IG).

ered an eminent amount of reactions, steering the

measurements away from the actual picture. In order

to prevent this phenomenon, the distribution of all the

available measures was thoroughly examined. This

process highlighted the outliers in the dataset, which

were then excluded to ensure the reliability of the ﬁ-

nal conclusions.

4 DATA ANALYSIS RESULTS

In this section, we extensively present the results of

our research.

4.1 Instagram Results

Concerning IG, it has ﬁrmly established itself in the

Greek community and, especially, in the younger

users, with the majority of which being active on the

platform for more than two years (point of reference

is the year 2020). However, the ongoing entry of more

older users in the platform proves its increasing rate

of inﬂuence on the whole age spectrum of the com-

munity. The following ﬁndings hold.

• IG is a platform on which female users obtain

signiﬁcant attention, as they gathered the largest

number of followers within 2020, with male users

following second in the ranking.

• The higher inﬂuence rate marked by female/male

accounts signiﬁes that platform users are more

strongly related to personal accounts (Fig. 1).

• Businesses hold a strict attitude regarding the

number of accounts they follow; similar is the at-

titude of the female accounts (Fig. 2).

• Business and female accounts were leading in

number of posts during 2020 (Fig. 3).

• Male users stayed less active, maintaining a rela-

tively low content production rate.

• In summer of 2020 male and female content cre-

ators highly boosted their activity level.

DATA 2022 - 11th International Conference on Data Science, Technology and Applications

222

Figure 2: Avg following per account category (IG).

Figure 3: Num of posts per month and account cat (IG).

Moreover, the upload of posts related to lifestyle, trav-

elling and fashion/beauty during 2020 was signiﬁ-

cantly frequent, proving that IG provides a fertile

ground for the development of such content. How-

ever, each category of content creators prospered in

different thematic categories as follows. Female cre-

ators and the business accounts presented high con-

tent creation rate in the fashion/beauty ﬁeld, male

creators showed a preference towards travelling con-

tent, while the uncategorised accounts created posts

in a wider spectrum of thematic categories, including

travelling, arts and entertainment.

Taking also into consideration the answers to our

survey, we concluded that the Greek community was

particularly interested in lifestyle, arts, travelling,

and entertainment during 2020. Nevertheless, male

and female social media users expressed some spe-

cial interests, with the ﬁrst showing a preference to

sports and technology, while the latter prefering fash-

ion/beauty and cooking. Moreover, remarkable was

the presence of contests (also known as Giveaways)

in the Greek social media community. The organ-

isation of numerous Giveaways by content creators

with various interests, in combination with the huge

engagement of the audience (regardless of the users’

age) with these posts, led us to the conclusion that

Giveaways were the most popular type of IG posts

for the year 2020 (Fig. 4).

4.2 YouTube Results

Concerning YT, it is quite different from IG. The shar-

ing and playback of videos form the main pillar of this

Figure 4: Avg engagement per post type (IG).

platform, while it is gradually adopting many modern

social media features, such as the capability of up-

loading text posts and highlights. Considering that

YT pre-existed IG, the Greek audience seems to have

a high degree of familiarity with the character of the

platform, as users of all ages have been using it for

more than two years (point of reference is the year

2020). Nonetheless, despite the multiannual presence

of elder users on the platform, it appears that YT is

being better absorbed by younger age groups. The en-

gagement of Greek users’ daily lives with YT can be

also inferred from the frequent watch of videos in the

platform. However, the more time required to interact

with the YT content, compared to IG, has resulted in

the partial shift of users to the weekly use of the plat-

form, as opposed to the daily browsing through IG.

The following ﬁndings hold.

• Male creators and uncategorised channels have a

stronger presence when compared with the num-

ber of channels administrated by female creators

and businesses.

• Male creators and uncategorised channels have

the highest number of subscriptions.

• Greek businesses marked the lowest engagement

rate with their audience within 2020, as well as the

highest rate of “Dislike” reactions on their videos.

• Channels administrated by male and female users

had a better engagement with their subscribers,

signifying that personalised channels establish a

stronger relationship with the community (Fig. 5).

• Newly established channels also marked high en-

gagement rates, implying that newer content cre-

ators cover the modern needs of the Greek YT

community more effectively (Fig. 6).

• Male creators and uncategorised channels were

the most active on the platform.

• The overall production rate was signiﬁcantly in-

creased in 2020.

• Creators’ productivity did not meet the need of the

community to engage with the uploaded content

during the summer months.

From Digital Footprints to Facts: Mining Marketing Policies of the Greek Community on Instagram and Youtube

223

Figure 5: Avg engagement per account category (YT).

Figure 6: Avg engagement per year of channel creation

(YT).

• Entertainment, comedy, news, gaming, and mu-

sic were the thematic categories that included the

highest number of uploaded videos, with the ﬁrst

three showing a remarkable growth.

It is worth mentioning that each category of creators

distinguished itself in the creation of videos related to

speciﬁc thematic categories. In more detail, a large

share of videos uploaded by male creators and un-

categorised channels was focused on comedy, gaming

and music, female creators uploaded content mainly

related to lifestyle, fashion/beauty and cooking, while

businesses exhibited a more diverse character, since

their uploaded content was mainly concerning tech-

nology, ﬁtness, gaming, and comedy.

Concerning the community’s engagement with the

thematic categories within 2020, it applies that (i)

gaming, comedy, entertainment, arts and educational

content comprised poles of great interest, (ii) news

and politics videos received negative response, hold-

ing the record for the highest average number of “Dis-

like” reactions, (iii) gaming, entertainment, and peo-

ple & blogs formed the fundamental thematic cate-

gories of videos created by channels established in

2020, (iv) videos that include the active participation

of viewers (i.e., QnAs, challenges, “We’re reacting to

your stories”), as well as exhibition of products (i.e.,

reviews, haul, unboxing) obtained signiﬁcant atten-

tion (Fig. 7), (v) videos that feature highlights from

the creator’s daily life (Vlog) were remarkably pop-

ular (Fig. 7), (vi) contest videos (Giveaways) were

found to be less prevalent on YT than on the IG plat-

form, but they did achieve a quite high engagement

rate (Fig. 7).

Figure 7: Avg engagement per video type (YT).

Figure 8: IG posts per day and hour (Businesses).

4.3 Business and Inﬂuencer Marketing

Since one of the fundamental axes of our research is

the study of business presence on social media, we

thoroughly examined their activity on the platforms.

It appeared that IG provides a fertile ground for the

development of commercial relationships, as it has

managed to attract a multitude of businesses, which,

in fact, follow a fairly intense activity. On the other

hand, numerous businesses are also present on YT,

although to a more limited extend when compared

to IG. Businesses exhibit the following common fea-

tures in both platforms.

• Transportation businesses (i.e., ferry companies,

airlines, etc.) hold a relatively small portion

(<5% for IG and <3,5% for YT) of the Greek

companies having presence on social platforms.

• Businesses present a conservative and profes-

sional character on social media platforms, since

they mostly adher a consistent activity weekly

schedule and follow sparingly other user accounts

(Figs. 2 and 8).

• Businesses remarkably increase their activity dur-

ing holidays, celebrations and anniversaries, such

as Easter, summer, Christmas or Valentine’s Day,

indicating that these are periods of increased com-

mercial interest (Fig. 3).

• Businesses have not achieved yet to establish a

committed community, as it was shown that Greek

social media users maintained a poor engagement

rate with content uploaded by businesses during

2020 (Figs. 1 and 5).

In order for businesses to promote their content on so-

cial media more effectively, they either advertise it via

DATA 2022 - 11th International Conference on Data Science, Technology and Applications

224

regular posts/videos or paid promotions, or have their

content promoted by popular content creators (IM). In

more detail:

• The exposure of the advertised content to a group

of users that are not followers or subscribers of the

corresponding business leads to low engagement

rates as well as, in some cases, to users’ feeling of

annoyance.

• The Greek IG community appeared to be more

tolerant to advertisements compared to YT.

• Regular advertising via posts/videos or paid pro-

motions was observed to exert a higher inﬂuence

rate on elder social media users.

• The high rates of audience’s engagement with

content that included product placement within

2020 was the reason why numerous businesses

turned to popular content creators for promotion

(Figs. 4 and 7).

• IM was observed to have greater inﬂuence on

younger social media users.

As already discussed, the differences between IG

and YT platforms have favoured the development of

different thematic categories and content types on

each platform. This has shaped the business tac-

tics on social media as follows: (i) businesses on

IG expressed their preference towards female con-

tent creators, who mostly uploaded content related

to lifestyle, (ii) businesses on IG were mostly inter-

ested in fashion and beauty, (iii) at YT male content

creators were at the centre of attention of businesses,

and (iv) the interests of businesses on YT were gam-

ing, science/technology, fashion/beauty, and travel-

ling. Finally, it is worth mentioning that the activ-

ity of businesses on IG was inﬂuential across a wide

age range, in contrast to YT, where businesses corre-

sponded to the needs of a younger audience.

4.4 Impact of COVID-19

Year 2020 was the one that brought several major

changes to peoples’ daily lives, as it was the period

during which the COVID-19 virus broke out. In the

context of seeking for a more accurate view of this

impact, the following observations were made.

• COVID-19 led to a bigger shift of users towards

social media, with a large part of the Greek com-

munity using a plethora of hashtags related to the

pandemic; few popular hashtags were actually ac-

companied by a feeling of nostalgia and reminis-

cence (e.g., #throwback, #memories).

• It was noticed that the ﬁrst wave of the pan-

demic (March 2020-May 2020) had a greater im-

Figure 9: Most used IG hashtags during 03/2020-05/2020.

Figure 10: Most used IG hashtags during 11/2020-12/2020.

Figure 11: YT videos per month.

pact on the public, with the second phase (Octo-

ber 2020-December 2020) being associated with a

weakened but noticeable awareness among users

(Figs. 9 and 10).

• YT had a clear beneﬁt from this situation, with a

sharp increase in the number of uploaded videos

throughout 2020 (Fig. 11).

• The increased activity of users on social media, in

combination with the suspension of several busi-

ness operations, provided an opportunity for busi-

nesses to enhance, or even build from scratch,

their digital presence on social media platforms.

• Certain thematic categories were also boosted

during the pandemic; gaming, entertainment,

comedy and news & politics where sectors whose

productivity increased signiﬁcantly.

5 CONCLUSIONS AND FUTURE

WORK

In this work, we have presented a study concerning

the interference of commerce with popular social me-

dia platforms discerning three fundamental axes: (i)

From Digital Footprints to Facts: Mining Marketing Policies of the Greek Community on Instagram and Youtube

225

the common users’ digital behaviour, (ii) the inﬂu-

encers’ digital behaviour, and (iii) the interest of com-

panies to draw marketing policies grounded on these

behaviours. This is the ﬁrst study concerning the

activity of the Greek community on Instagram and

YouTube platforms, the activity of Greek companies

on social media, and the impact of Covid-19 on Greek

consumers’ digital behaviour.

This work can be further extended by investigating

more social network platforms. Moreover, we envi-

sion a general framework for collecting and analysing

data from social platforms with minimum user inter-

vention and by using ﬁlters per country, per topic,

and/or per social network. Having such a framework,

it would be of great interest to compare data coming

from different communities and generalise our con-

clusions concerning the interplay of businesses with

popular social media platforms.

ACKNOWLEDGEMENTS

This work was supported in part by project

ENIRISST+ under grant agreement No. MIS

5047041 from the General Secretary for ERDF & CF,

under Operational Programme Competitiveness, En-

trepreneurship and Innovation 2014-2020 (EPAnEK)

of the Greek Ministry of Economy and Development

(co-ﬁnanced by Greece and the EU through the Euro-

pean Regional Development Fund).

REFERENCES

Acikgoz, F. and Burnaz, S. (2021). The inﬂuence of ‘in-

ﬂuencer marketing’ on youtube inﬂuencers. Int. J. of

Internet Marketing and Advertising, 15(2):201–219.

Advertising, R. (2019). Rakuten marketing 2019 inﬂuencer

marketing global survey. https://www.iab.com/wp-

content/uploads/2019/03/Rakuten-2019-Inﬂuencer-

Marketing-Report-Rakuten-Marketing.pdf. [Online;

accessed 24-January-2022].

Asdecker, B., Landwehrjohann, M., Vornberger, K., and

Vogel, Y. (2021). Inﬂuencer marketing on instagram:

Exploring the role of travel and other factors on a

post’s success. In Proc. of the 50th European Mar-

keting Academy Conf. (EMAC).

Boerman, S. and M

uller, C. (2021). Understanding which

cues people use to identify inﬂuencer marketing on

instagram: an eye tracking study and experiment. Int.

J. of Advertising, pages 1–24.

Boerman, S. and van Reijmersdal, E. (2020). Disclosing in-

ﬂuencer marketing on youtube to children: The mod-

erating role of para-social relationship. Frontiers in

Psycology.

Carreon, N. (2019). Youtube inﬂuencer marketing: A qual-

itative research of danish youtube inﬂuencers in an in-

ternational perspective. Master’s thesis, Copenhagen

Business School.

Casal

o, L. V., Flavi

an, C., and Ib

nez-S

anchez, S. (2020).

Inﬂuencers on instagram: Antecedents and conse-

quences of opinion leadership. J. of Business Re-

search, 117:510–519.

Chen, Z., Lu, H., and Li, L. (2021). How new media market-

ing inﬂuence consumers’ purchase behavior in the era

of big data. In Proc. of the Int. Conf. on Cyber Security

Intelligence and Analytics (CSIA), pages 601–606.

Coates, A., Hardman, C., Halford, J., Christiansen, P., and

Boyland, E. (2020). It’s just addictive people that

make addictive videos: Children’s understanding of

and attitudes towards inﬂuencer marketing of food and

beverages by youtube video bloggers. Int. J. of Envi-

ronmental Research and Public Health, 17(2).

Djafarova, E. and Bowes, T. (2021). ‘instagram made me

buy it’: Generation z impulse purchases in fashion in-

dustry. J. of Retailing and Consumer Services, 59.

Djafarova, E. and Rushworth, C. (2017). Exploring the

credibility of online celebrities’ instagram proﬁles in

inﬂuencing the purchase decisions of young female

users. Computers in Human Behavior, 68:1–7.

Dreghorn, B. (2020). What is the difference

between the 3 instagram proﬁle types.

https://www.business2community.com/instagram/what-

is-the-difference-between-the-3-instagram-proﬁle-

types-02300390. [Online; accessed 28-January-

2022].

Eirinaki, M., Gao, J., Varlamis, I., and Tserpes, K.

(2018). Recommender systems for large-scale social

networks: A review of challenges and solutions. Fu-

ture Generation Computer Systems, 78:413–418.

Lin, R.-H., Jan, C., and Chuang, C.-L. (2019). Inﬂuencer

marketing on instagram. Int. J. of Innovation in Man-

agement, 7(1):33–41.

Peng, S., Zhou, Y., Cao, L., Yu, S., Niu, J., and Jia, W.

(2018). Inﬂuence analysis in social networks: A

survey. J. of Network and Computer Applications,

106:17–32.

Prasad, R. (2018). Youtube videos as an effective medium

in branding - a study among urban women in mysuru

city. Int. J. of Mechanical Engineering and Technol-

ogy (”IJMET”), 9(7):397–408.

Schwemmer, C. and Ziewiecki, S. (2018). Social media

sellout: The increasing role of product promotion on

youtube. Social Media and Society.

Sehl, K. and Tien, S. (2020). 6 ways to calcu-

late engagement rate. https://blog.hootsuite.com/

calculate-engagement-rate/. [Online; accessed 20-

December-2020].

Vrontis, D., Makrides, A., Christoﬁ, M., and Thrassou, A.

(2021). Social media inﬂuencer marketing: A system-

atic review, integrative framework and future research

agenda. Int. J. of Consumer Studies, 45.

Wang, W. and Street, W. (2018). Modeling and maximizing

inﬂuence diffusion in social networks for viral mar-

keting. Applied Network Science, 3(6).

Xiao, M., Wang, R., and Chan-Olmsted, S. M. (2018). Fac-

tors affecting youtube inﬂuencer marketing credibil-

ity: a heuristic-systematic model. J. of Media Busi-

ness Studies, 15:188–213.

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