Flickr Web 2.0: Analysis of Photo Sharing, Tagging and User Behavior
VerifiedAdded on 2020/06/06
|9
|2543
|168
Report
AI Summary
This report provides an in-depth analysis of Flickr Web 2.0, examining its functionality, tagging behavior, and impact on amateur photography and online communities. The study explores Flickr's evolution from an innovative social game to a more commercially driven platform, assessing its role in citizen journalism and vernacular creativity. It investigates tag behavior, Flickr groups, and the broader context of amateur photography, considering the platform's strengths and limitations. The report also addresses the commercial influences, digital divides, and interactivity levels within Flickr. The analysis includes the experimental setup, photo collection, and the analysis of Flickr groups, with a focus on datasets, information analysis, and searching by labels using topic models. The conclusion highlights the potential of interpersonal labeling systems and the importance of understanding user incentives and motivations within the context of Flickr's operational techniques and its place within the systematics of the subject field.
Contribute Materials
Your contribution can guide someone’s learning journey. Share your
documents today.

Flickr Web 2.0
Secure Best Marks with AI Grader
Need help grading? Try our AI Grader for instant feedback on your assignments.

ABSTRACT
The particular “photo sharing” site Flickr is among the most commonly cited examples
utilized to define Web2. 0. This particular paper aims to explore exactly where Flickr's real
novelty is situated, examining its functionality and the place in the world of amateur pictures.
Several optimistic sights of the impact of Reddit such as its facilitation associated with citizen
journalism, “vernacular creativity” and in learning as an “affinity space” are evaluated.
Flickr's development path passes through an innovative social game to some relatively familiar
model of a website, itself developed through extreme user participation but afterwards stabilizing
with the reassertion of the commercial relationship to the regular membership. The broader
context from the impact of Flickr is usually examined by looking at the establishments of
amateur photography plus particularly the code of pictorials promoted by the clubs plus industry
during the twentieth hundred years. The nature of Flickr being a benign space is premised on the
way the democratic possible of photography is managed by such institutions. The particular
limits of optimistic statements about Flickr are discovered in the way that the system is made to
satisfy commercial purposes, ongoing digital divides in entry and the low interactivity plus
criticality on Flickr.
The particular “photo sharing” site Flickr is among the most commonly cited examples
utilized to define Web2. 0. This particular paper aims to explore exactly where Flickr's real
novelty is situated, examining its functionality and the place in the world of amateur pictures.
Several optimistic sights of the impact of Reddit such as its facilitation associated with citizen
journalism, “vernacular creativity” and in learning as an “affinity space” are evaluated.
Flickr's development path passes through an innovative social game to some relatively familiar
model of a website, itself developed through extreme user participation but afterwards stabilizing
with the reassertion of the commercial relationship to the regular membership. The broader
context from the impact of Flickr is usually examined by looking at the establishments of
amateur photography plus particularly the code of pictorials promoted by the clubs plus industry
during the twentieth hundred years. The nature of Flickr being a benign space is premised on the
way the democratic possible of photography is managed by such institutions. The particular
limits of optimistic statements about Flickr are discovered in the way that the system is made to
satisfy commercial purposes, ongoing digital divides in entry and the low interactivity plus
criticality on Flickr.

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................1
TAG BEHAVIOUR ........................................................................................................................1
Photo Collection..........................................................................................................................2
Common Tag Characteristics......................................................................................................2
EXPERIMENTAL SET UP.............................................................................................................2
Task.............................................................................................................................................2
Photo Collection..........................................................................................................................3
FLICKR GROUPS..........................................................................................................................3
ANALYSIS ASSOCIATED WITH FLICKR GROUPS................................................................4
Datasets.......................................................................................................................................4
Information Analysis...................................................................................................................4
Searching by Labels Using the Topic Model..............................................................................4
CONCLUSION................................................................................................................................4
REFERENCES................................................................................................................................5
INTRODUCTION...........................................................................................................................1
TAG BEHAVIOUR ........................................................................................................................1
Photo Collection..........................................................................................................................2
Common Tag Characteristics......................................................................................................2
EXPERIMENTAL SET UP.............................................................................................................2
Task.............................................................................................................................................2
Photo Collection..........................................................................................................................3
FLICKR GROUPS..........................................................................................................................3
ANALYSIS ASSOCIATED WITH FLICKR GROUPS................................................................4
Datasets.......................................................................................................................................4
Information Analysis...................................................................................................................4
Searching by Labels Using the Topic Model..............................................................................4
CONCLUSION................................................................................................................................4
REFERENCES................................................................................................................................5

INTRODUCTION
In today's era, there are various changes made through technology that are seen in
business and marketing. Traditional heritage institutions and museums that were limited to
certain areas has now expanded to global level using the social media networking. Using the
services they have influenced large numbers of customer that like art, artefacts and other
traditional monuments. There are various social networking services such as Flickr, 500px.,
DeviantArt and Instagram that helps in online photo-sharing system using which the individual
can describe their images, make collage, videos and many other things of their choices. Flicker
is similar such social-media networking site but with better features. As per the account holder
setting, picture posted on the Reddit by them are downloaded, seen, searched, tagged and even
other person can comment on them by the person using it. The above activities helps others to
overview those images substantially based on different parameters and people can select
different things from there and can purchase from that person. Using the same methods museums
and heritage institutions have manage to sell those things that are available with them or the
holdings of museums. It is an effective approach that has made potential changes in the ways
museums business can be enhanced without any restrictive boundaries (Cameron and Mangle,
2009). It also provides them to make online sale of different pictures and images and where
buyers were also getting warranty on such products.
Rich media reflex ion is another system that is used for the large scale collection at the
work practise. It is retrieval progression success that has been not yet succeeded but is presently
in state of art that is content based picture. Using the electronic technology the software are
linking the people and are decreasing the semantic distance between them. However, Reddit is
successfully among all of them as the users using it are prepared for the linguistics circumstances
through the mutual composer. Now a days users are using the motivational quotes and other text
so that people can access these photo more better manner. Along with this, there is another
feature, photo annotations that provides the personal viewpoint and context that shows crucial
relation between the image owner and the audience. Various pictures can be used by the people
and can be tagged using different quotations. It is similar to the memes which are accessed by
thousands of people and can be further used. Moreover, they can be annotated by another users
which can possible describe their work. Flickr is similar social media network that allows the
1
In today's era, there are various changes made through technology that are seen in
business and marketing. Traditional heritage institutions and museums that were limited to
certain areas has now expanded to global level using the social media networking. Using the
services they have influenced large numbers of customer that like art, artefacts and other
traditional monuments. There are various social networking services such as Flickr, 500px.,
DeviantArt and Instagram that helps in online photo-sharing system using which the individual
can describe their images, make collage, videos and many other things of their choices. Flicker
is similar such social-media networking site but with better features. As per the account holder
setting, picture posted on the Reddit by them are downloaded, seen, searched, tagged and even
other person can comment on them by the person using it. The above activities helps others to
overview those images substantially based on different parameters and people can select
different things from there and can purchase from that person. Using the same methods museums
and heritage institutions have manage to sell those things that are available with them or the
holdings of museums. It is an effective approach that has made potential changes in the ways
museums business can be enhanced without any restrictive boundaries (Cameron and Mangle,
2009). It also provides them to make online sale of different pictures and images and where
buyers were also getting warranty on such products.
Rich media reflex ion is another system that is used for the large scale collection at the
work practise. It is retrieval progression success that has been not yet succeeded but is presently
in state of art that is content based picture. Using the electronic technology the software are
linking the people and are decreasing the semantic distance between them. However, Reddit is
successfully among all of them as the users using it are prepared for the linguistics circumstances
through the mutual composer. Now a days users are using the motivational quotes and other text
so that people can access these photo more better manner. Along with this, there is another
feature, photo annotations that provides the personal viewpoint and context that shows crucial
relation between the image owner and the audience. Various pictures can be used by the people
and can be tagged using different quotations. It is similar to the memes which are accessed by
thousands of people and can be further used. Moreover, they can be annotated by another users
which can possible describe their work. Flickr is similar social media network that allows the
1
Secure Best Marks with AI Grader
Need help grading? Try our AI Grader for instant feedback on your assignments.

person to identify or discover various photos on the similar subject by various online users that
uses the tags system to popularize those images.
TAG BEHAVIOUR
On this section the Flickr is definitely described by us photograph accumulation used for
the assessment, and the account holder provide ideas in the photograph labelling behaviour of
users. There are two main tags question that users always need to access and which led others to
understand that why tagging is required. These questions are "How tags can be popularize?" and
"what are the popular tagging features?". Along with this, two questions there are various other
important things that needs to access within Flicker, “Why do individuals tag-pictures?”.
Moreover, flicker provides better option of personal and group tagging option than Facebook and
other similar sites.
Photo Collection
Flickr has more than 8.5 million users which uses photo-sharing service. People upload,
tag-picture and organized different things such as pictures, collages and videos. As per the
official details, the application is used to upload more than 2 million photos per days and near to
this people tags those pictures. Many researchers have identified that till now there are various
random snapshot uploaded, tagged and downloaded from the Reddit which accounts up to 52
million. However, the data would have increase as the process is continuous. The particular
picture uploading time was seen in the year 2004-2007 and definitely has increased till now. Till
now every user that is on flicker must have made their own user-defined tag.
Common Tag Characteristics
At the time of building tag recommendation strategies, for users, there are certain things
they need to analyse. These are how, why and exactly what individual are uploading and tagging.
Under this there is another important features that is needed to be accessed which is about the
how user do self-tagging. The sites have more than 52 million photos where tagging of more
than 188 million labels can be seen as-well-as 3.7 million unique taggers are there. Illustration 1
shows the subject matter of the taggers frequency on the log-log scale. On the X-axis there are
details about the unique tags which shows that more than 3.7 million unique tags, that have
descending tag regularity while the y-axis shows the particular tag frequency.
2
uses the tags system to popularize those images.
TAG BEHAVIOUR
On this section the Flickr is definitely described by us photograph accumulation used for
the assessment, and the account holder provide ideas in the photograph labelling behaviour of
users. There are two main tags question that users always need to access and which led others to
understand that why tagging is required. These questions are "How tags can be popularize?" and
"what are the popular tagging features?". Along with this, two questions there are various other
important things that needs to access within Flicker, “Why do individuals tag-pictures?”.
Moreover, flicker provides better option of personal and group tagging option than Facebook and
other similar sites.
Photo Collection
Flickr has more than 8.5 million users which uses photo-sharing service. People upload,
tag-picture and organized different things such as pictures, collages and videos. As per the
official details, the application is used to upload more than 2 million photos per days and near to
this people tags those pictures. Many researchers have identified that till now there are various
random snapshot uploaded, tagged and downloaded from the Reddit which accounts up to 52
million. However, the data would have increase as the process is continuous. The particular
picture uploading time was seen in the year 2004-2007 and definitely has increased till now. Till
now every user that is on flicker must have made their own user-defined tag.
Common Tag Characteristics
At the time of building tag recommendation strategies, for users, there are certain things
they need to analyse. These are how, why and exactly what individual are uploading and tagging.
Under this there is another important features that is needed to be accessed which is about the
how user do self-tagging. The sites have more than 52 million photos where tagging of more
than 188 million labels can be seen as-well-as 3.7 million unique taggers are there. Illustration 1
shows the subject matter of the taggers frequency on the log-log scale. On the X-axis there are
details about the unique tags which shows that more than 3.7 million unique tags, that have
descending tag regularity while the y-axis shows the particular tag frequency.
2

EXPERIMENTAL SET UP
This section is about the 4-tag recommendation strategies which are evaluated using the
empirical evaluation. The experimental set-ups are highlighted, system optimization are
concluded and based on those outcomes evaluation are mentioned.
Task
In the above sections we have discussed about the following task: Provided picture
uploaded on Flickr as well as a set of user-defined tags. The application has provided the better
and effective description of the images and photograph. As per our finding we have considered it
as rating problems, i.e., the machine automatically collects the selected tags that are labelled as
simply having great descriptor for the photo. Within an functional setting, this kind of
applications are recognized to present the particular suggested tags that belongs to consumer, in a
way that person can chose from particular notation by selecting the tags that are mentioned in the
list tags.
Photo Collection
In order to conduct the assessment there were 331 pictures were selected through the
Flickr API. The particular chosen photos can be related to any topic which the application wants,
however most of them were found to be from basketball player, landscape, mountains, memes,
Iceland and sailing that were chose by the assessors and most popular in the tagging or were
most recommended. Further, they mention about the necessary post and picture that they have to
judge, for which they have considered the framework of the pictures.
Additionally, we all have ensured that the picture that had been equally apportioned over
the various label classes as described in Tabular way in which table 1 associated with Section-3,
to have variant in the completeness of the reflex ion. Other than the 2-manipulations, the
particular image selection process has been randomized.
FLICKR GROUPS
In English dictionary there are various meaning of the "group", however when individual
is finding one similar to the Reddit groups and the definition that perfectly defines it are:
o “A gathering of individuals or aim gathered or even situated Unitedly”;
o “Gathering of individuals that makes single unity and has come all-together because
of sameness”.
3
This section is about the 4-tag recommendation strategies which are evaluated using the
empirical evaluation. The experimental set-ups are highlighted, system optimization are
concluded and based on those outcomes evaluation are mentioned.
Task
In the above sections we have discussed about the following task: Provided picture
uploaded on Flickr as well as a set of user-defined tags. The application has provided the better
and effective description of the images and photograph. As per our finding we have considered it
as rating problems, i.e., the machine automatically collects the selected tags that are labelled as
simply having great descriptor for the photo. Within an functional setting, this kind of
applications are recognized to present the particular suggested tags that belongs to consumer, in a
way that person can chose from particular notation by selecting the tags that are mentioned in the
list tags.
Photo Collection
In order to conduct the assessment there were 331 pictures were selected through the
Flickr API. The particular chosen photos can be related to any topic which the application wants,
however most of them were found to be from basketball player, landscape, mountains, memes,
Iceland and sailing that were chose by the assessors and most popular in the tagging or were
most recommended. Further, they mention about the necessary post and picture that they have to
judge, for which they have considered the framework of the pictures.
Additionally, we all have ensured that the picture that had been equally apportioned over
the various label classes as described in Tabular way in which table 1 associated with Section-3,
to have variant in the completeness of the reflex ion. Other than the 2-manipulations, the
particular image selection process has been randomized.
FLICKR GROUPS
In English dictionary there are various meaning of the "group", however when individual
is finding one similar to the Reddit groups and the definition that perfectly defines it are:
o “A gathering of individuals or aim gathered or even situated Unitedly”;
o “Gathering of individuals that makes single unity and has come all-together because
of sameness”.
3

An organization is a collection of individuals/things therefore, that is either in social
closeness or shares some fuzzy logic. People on Flickr, based on the technical perspective,
groupings are aggregation of customers that feels freely in joining such community. Aim of
groupings is to assist the revealing of individual picture known as group pool. It can be any tag
that one person has made to other. Besides this, all the taggers tags the picture that turn out to be
belonging of group picture of swimming photo.
There are various types of groups and even some of them can be intertwined. A short,
non-exhaustive database is shown below:
o Demographical organizations: Global Photo or journalism, picture of different location
areas or places. It can also be of some specific location like New York City and similar
other popular cities.
o Content groups: Artistic Photography; that makes focus on the particular sections such as
animals in their natural environment, or of social areas.
o Visual style groups: It is specific technique by which picture are created, one example is
Life in White plus Black, Closer plus Closer-Macro Photography.
ANALYSIS ASSOCIATED WITH FLICKR GROUPS
Datasets
After gathering information from Flickr’s API and studying it. If users have restrictive
privacy then picture can not be accessed, however, for those having the public accounts their
details available publicly available to all the people. This particular private information was not
available to all of us for this study.
Information Analysis
All the details that are mentioned in this reports shows the structure and features that are
shown by the Flicker community. People that are not the users of the Reddit have to chose other
option to upload the pictures and different usable styles at same times.
Searching by Labels Using the Topic Model
There is difficulty in finding the images that are on the Flicker as for the research there is
requirement of the titles and description. Group tagging names are normally descriptive but
cannot be used for all the photos. It may help forward for the team discovery. It can be made in
two way process; first finding the keywords and getting results on the particular parts. It is not
similar to the direct label searching as it is based on the disambiguation information which uses
4
closeness or shares some fuzzy logic. People on Flickr, based on the technical perspective,
groupings are aggregation of customers that feels freely in joining such community. Aim of
groupings is to assist the revealing of individual picture known as group pool. It can be any tag
that one person has made to other. Besides this, all the taggers tags the picture that turn out to be
belonging of group picture of swimming photo.
There are various types of groups and even some of them can be intertwined. A short,
non-exhaustive database is shown below:
o Demographical organizations: Global Photo or journalism, picture of different location
areas or places. It can also be of some specific location like New York City and similar
other popular cities.
o Content groups: Artistic Photography; that makes focus on the particular sections such as
animals in their natural environment, or of social areas.
o Visual style groups: It is specific technique by which picture are created, one example is
Life in White plus Black, Closer plus Closer-Macro Photography.
ANALYSIS ASSOCIATED WITH FLICKR GROUPS
Datasets
After gathering information from Flickr’s API and studying it. If users have restrictive
privacy then picture can not be accessed, however, for those having the public accounts their
details available publicly available to all the people. This particular private information was not
available to all of us for this study.
Information Analysis
All the details that are mentioned in this reports shows the structure and features that are
shown by the Flicker community. People that are not the users of the Reddit have to chose other
option to upload the pictures and different usable styles at same times.
Searching by Labels Using the Topic Model
There is difficulty in finding the images that are on the Flicker as for the research there is
requirement of the titles and description. Group tagging names are normally descriptive but
cannot be used for all the photos. It may help forward for the team discovery. It can be made in
two way process; first finding the keywords and getting results on the particular parts. It is not
similar to the direct label searching as it is based on the disambiguation information which uses
4
Paraphrase This Document
Need a fresh take? Get an instant paraphrase of this document with our AI Paraphraser

the synonymy of the keywords. Allow us to illustrate the described technique with the results for
the expression “portrait”. Number 10 shows a histogram of the topics’ probabilities for that tag
“portrait”, and the very first five topic-expert groups for your top four most possible topics.
CONCLUSION
Interpersonal labelling systems have the sustainability to enhance on earlier outcomes to
numerous well-defined and studied information and internet systems issues. It can be
personalized issues or can be related to the link analysis, forming details, determining
homonyms and synonyms, building-networks associated with belongings to engagement
hyperlink spam, monitoring trends plus drift in information techniques and more. The potential
associated with rationale about tags, customers, as-well-as potential resources in oneness are
promoting. To understand operational techniques, research workers should make observation on
system’s location within the systematics of subject field delineated in Section several. Research
should consider the incentives and motivations so that people can be inspired. Within studying
Flickr, the author demonstrated that physical connection and participation varies according to
patients of Del. icier. So, De and Flickr. There are variation in the dimensions of our own
categorization rather. Furthermore, the particular incentive models of Flickr plus all of us are
considerably disparate, that are expected for the different sections’ output. Hopefully those
system makers have to consider those architectonic their marking scheme. Lastly, there is no
completely description about the topic as it is very elongated topic. Brand current users for
tagging techniques are developed every complete day; person that are related with such things
should make fixed targets, causative, and aim.
5
the expression “portrait”. Number 10 shows a histogram of the topics’ probabilities for that tag
“portrait”, and the very first five topic-expert groups for your top four most possible topics.
CONCLUSION
Interpersonal labelling systems have the sustainability to enhance on earlier outcomes to
numerous well-defined and studied information and internet systems issues. It can be
personalized issues or can be related to the link analysis, forming details, determining
homonyms and synonyms, building-networks associated with belongings to engagement
hyperlink spam, monitoring trends plus drift in information techniques and more. The potential
associated with rationale about tags, customers, as-well-as potential resources in oneness are
promoting. To understand operational techniques, research workers should make observation on
system’s location within the systematics of subject field delineated in Section several. Research
should consider the incentives and motivations so that people can be inspired. Within studying
Flickr, the author demonstrated that physical connection and participation varies according to
patients of Del. icier. So, De and Flickr. There are variation in the dimensions of our own
categorization rather. Furthermore, the particular incentive models of Flickr plus all of us are
considerably disparate, that are expected for the different sections’ output. Hopefully those
system makers have to consider those architectonic their marking scheme. Lastly, there is no
completely description about the topic as it is very elongated topic. Brand current users for
tagging techniques are developed every complete day; person that are related with such things
should make fixed targets, causative, and aim.
5

REFERENCES
[1] Baeza-Yates, R. and Ribeiro-Neto, B.. Modern Information Retrieval. Addison-Wesley,
1999.
[2] Brieger, R.L., 1991. Explorations in Structural Analysis: Dual and Multiple Networks of
Social Structure. New York: Garland Press.
[3] Breese, J.S., Heckermen, D. and Kadie, C.M. Empirical analysis of predictive algorithms for
collaborative filtering. Microsoft Research Technical Report, (MSR-TR-98-12), October 1998.
[4] Burt, R. 1992. Structural Holes: The Social Structure of Competition. Cambridge, MA:
Harvard University Press.
[5] Chakrabarti, S., Dom, B., Raghavan, P., Rajagopalan, S., Gibson, D., and Kleinberg, J. 1998.
Automatic resource compilation by analyzing hyperlink structure and associated text. In
Proceedings of the Seventh international Conference on World Wide Web 7 (Brisbane,
Australia).
[6] Coates, T. Two cultures of fauxonomies collide. June 4 2005.
http://www.plasticbag.org/archives/2005/06/two_cultures_of_fauxonomies_collide.shtml
[7] Freeman, L. C. 1979. Centrality in Social Networks: Conceptual Clarification. Social
Networks. 1, 215-239
[8] Furnas, G. W., Landauer, T. K., Gomez, L. M., and Dumais, S. T. The vocabulary problem in
human-system communication. Commun. ACM 30, 11 (1987).
[9] Golder, S., and Huberman, B. A. The Structure of Collaborative Tagging Systems. HP Labs
technical report, 2005. Available from http://www.hpl.hp.com/research/idl/papers/tags/
6
[1] Baeza-Yates, R. and Ribeiro-Neto, B.. Modern Information Retrieval. Addison-Wesley,
1999.
[2] Brieger, R.L., 1991. Explorations in Structural Analysis: Dual and Multiple Networks of
Social Structure. New York: Garland Press.
[3] Breese, J.S., Heckermen, D. and Kadie, C.M. Empirical analysis of predictive algorithms for
collaborative filtering. Microsoft Research Technical Report, (MSR-TR-98-12), October 1998.
[4] Burt, R. 1992. Structural Holes: The Social Structure of Competition. Cambridge, MA:
Harvard University Press.
[5] Chakrabarti, S., Dom, B., Raghavan, P., Rajagopalan, S., Gibson, D., and Kleinberg, J. 1998.
Automatic resource compilation by analyzing hyperlink structure and associated text. In
Proceedings of the Seventh international Conference on World Wide Web 7 (Brisbane,
Australia).
[6] Coates, T. Two cultures of fauxonomies collide. June 4 2005.
http://www.plasticbag.org/archives/2005/06/two_cultures_of_fauxonomies_collide.shtml
[7] Freeman, L. C. 1979. Centrality in Social Networks: Conceptual Clarification. Social
Networks. 1, 215-239
[8] Furnas, G. W., Landauer, T. K., Gomez, L. M., and Dumais, S. T. The vocabulary problem in
human-system communication. Commun. ACM 30, 11 (1987).
[9] Golder, S., and Huberman, B. A. The Structure of Collaborative Tagging Systems. HP Labs
technical report, 2005. Available from http://www.hpl.hp.com/research/idl/papers/tags/
6
1 out of 9

Your All-in-One AI-Powered Toolkit for Academic Success.
+13062052269
info@desklib.com
Available 24*7 on WhatsApp / Email
Unlock your academic potential
© 2024 | Zucol Services PVT LTD | All rights reserved.