This document summarizes the results of a survey about social media usage among young Europeans. Key findings include:
- Facebook was the most widely used social network across all countries surveyed. However, some countries had prominent national social networks like StudiVZ in Germany.
- Usage of social networks was nearly universal among respondents except in Romania where only 85% used them.
- Frequency of usage was very high, with most respondents accessing their primary social network multiple times per day or once per day.
- Reasons for not using social networks varied but included lack of interest, perceiving them as useless or a waste of time, and not wanting to develop online relationships.
Twitter Based Outcome Predictions of 2019 Indian General Elections Using Deci...Ferdin Joe John Joseph PhD
Presented at the 4th International Conference on Information Technology InCIT 2019 organised by Thai-Nichi Institute of Technology and Council of IT Deans in Thailand (CITT)
This is a presentation given at the ICWSM 2010 in Washington, DC (www.icwsm.org). You can watch a video of the presentation on videolectures.net
Twitter is a microblogging website where users read and write millions of short messages on a variety of topics every day. This study uses the context of the German federal election to investigate whether Twitter is used as a forum for political deliberation and whether online messages on Twitter validly mirror offline political sentiment. Using LIWC text analysis software, we conducted a content-analysis of over 100,000 messages containing a reference to either a political party or a politician. Our results show that Twitter is indeed used extensively for political deliberation. We find that the mere number of messages mentioning a party reflects the election result. Moreover, joint mentions of two parties are in line with real world political ties and coalitions. An analysis of the tweets’ political sentiment demonstrates close correspondence to the parties' and politicians’ political positions indicating that the content of Twitter messages plausibly reflects the offline political landscape. We discuss the use of microblogging message content as a valid indicator of political sentiment and derive suggestions for further research.
PREDICTING ELECTION OUTCOME FROM SOCIAL MEDIA DATAkevig
In this era of technology, enormous Online Social Networking Sites (OSNs) have arisen as a medium of
expressing any opinions, thoughts towards anything even support their status against any social or
political matter at the same time. Nowadays, people connected to those networks are more likely to prefer
to employ themselves utilizing these online platforms to exhibit their standings upon any political
organizations participating in the election throughout the whole election period. The aim of this paper is to
predict the outcome of the election by engaging the tweets posted on Twitter pertaining to the Australian
federal election-2019 held on May 18, 2019. We aggregated two efficacious techniques in order to extract
the information from the tweet data to count a virtual vote for each corresponding political group. The
original results of the election closely match the findings of our investigation, published by the Australian
Electoral Commission.
PREDICTING ELECTION OUTCOME FROM SOCIAL MEDIA DATAkevig
In this era of technology, enormous Online Social Networking Sites (OSNs) have arisen as a medium of expressing any opinions, thoughts towards anything even support their status against any social or political matter at the same time. Nowadays, people connected to those networks are more likely to prefer to employ themselves utilizing these online platforms to exhibit their standings upon any political organizations
participating in the election throughout the whole election period. The aim of this paper is to predict the outcome of the election by engaging the tweets posted on Twitter pertaining to the Australian federal election-2019 held on May 18, 2019. We aggregated two efficacious techniques in order to extract the
information from the tweet data to count a virtual vote for each corresponding political group. The original results of the election closely match the findings of our investigation, published by the Australian Electoral Commission.
PREDICTING ELECTION OUTCOME FROM SOCIAL MEDIA DATAijnlc
In this era of technology, enormous Online Social Networking Sites (OSNs) have arisen as a medium of expressing any opinions, thoughts towards anything even support their status against any social or political matter at the same time. Nowadays, people connected to those networks are more likely to prefer to employ themselves utilizing these online platforms to exhibit their standings upon any political organizations participating in the election throughout the whole election period. The aim of this paper is to predict the outcome of the election by engaging the tweets posted on Twitter pertaining to the Australian federal election-2019 held on May 18, 2019. We aggregated two efficacious techniques in order to extract the information from the tweet data to count a virtual vote for each corresponding political group. The original results of the election closely match the findings of our investigation, published by the Australian Electoral Commission.
Twitter Based Outcome Predictions of 2019 Indian General Elections Using Deci...Ferdin Joe John Joseph PhD
Presented at the 4th International Conference on Information Technology InCIT 2019 organised by Thai-Nichi Institute of Technology and Council of IT Deans in Thailand (CITT)
This is a presentation given at the ICWSM 2010 in Washington, DC (www.icwsm.org). You can watch a video of the presentation on videolectures.net
Twitter is a microblogging website where users read and write millions of short messages on a variety of topics every day. This study uses the context of the German federal election to investigate whether Twitter is used as a forum for political deliberation and whether online messages on Twitter validly mirror offline political sentiment. Using LIWC text analysis software, we conducted a content-analysis of over 100,000 messages containing a reference to either a political party or a politician. Our results show that Twitter is indeed used extensively for political deliberation. We find that the mere number of messages mentioning a party reflects the election result. Moreover, joint mentions of two parties are in line with real world political ties and coalitions. An analysis of the tweets’ political sentiment demonstrates close correspondence to the parties' and politicians’ political positions indicating that the content of Twitter messages plausibly reflects the offline political landscape. We discuss the use of microblogging message content as a valid indicator of political sentiment and derive suggestions for further research.
PREDICTING ELECTION OUTCOME FROM SOCIAL MEDIA DATAkevig
In this era of technology, enormous Online Social Networking Sites (OSNs) have arisen as a medium of
expressing any opinions, thoughts towards anything even support their status against any social or
political matter at the same time. Nowadays, people connected to those networks are more likely to prefer
to employ themselves utilizing these online platforms to exhibit their standings upon any political
organizations participating in the election throughout the whole election period. The aim of this paper is to
predict the outcome of the election by engaging the tweets posted on Twitter pertaining to the Australian
federal election-2019 held on May 18, 2019. We aggregated two efficacious techniques in order to extract
the information from the tweet data to count a virtual vote for each corresponding political group. The
original results of the election closely match the findings of our investigation, published by the Australian
Electoral Commission.
PREDICTING ELECTION OUTCOME FROM SOCIAL MEDIA DATAkevig
In this era of technology, enormous Online Social Networking Sites (OSNs) have arisen as a medium of expressing any opinions, thoughts towards anything even support their status against any social or political matter at the same time. Nowadays, people connected to those networks are more likely to prefer to employ themselves utilizing these online platforms to exhibit their standings upon any political organizations
participating in the election throughout the whole election period. The aim of this paper is to predict the outcome of the election by engaging the tweets posted on Twitter pertaining to the Australian federal election-2019 held on May 18, 2019. We aggregated two efficacious techniques in order to extract the
information from the tweet data to count a virtual vote for each corresponding political group. The original results of the election closely match the findings of our investigation, published by the Australian Electoral Commission.
PREDICTING ELECTION OUTCOME FROM SOCIAL MEDIA DATAijnlc
In this era of technology, enormous Online Social Networking Sites (OSNs) have arisen as a medium of expressing any opinions, thoughts towards anything even support their status against any social or political matter at the same time. Nowadays, people connected to those networks are more likely to prefer to employ themselves utilizing these online platforms to exhibit their standings upon any political organizations participating in the election throughout the whole election period. The aim of this paper is to predict the outcome of the election by engaging the tweets posted on Twitter pertaining to the Australian federal election-2019 held on May 18, 2019. We aggregated two efficacious techniques in order to extract the information from the tweet data to count a virtual vote for each corresponding political group. The original results of the election closely match the findings of our investigation, published by the Australian Electoral Commission.
Who’s in the Gang? Revealing Coordinating Communities in Social MediaDerek Weber
Political astroturfing and organised trolling are online malicious behaviours with significant real-world effects. Common approaches examining these phenomena focus on broad campaigns rather than the small groups responsible. To reveal networks of cooperating accounts, we propose a novel temporal window approach that relies on account interactions and metadata alone. It detects groups of accounts engaging in behaviours that, in concert, execute different goal-based strategies, which we describe. Our approach is validated against two relevant datasets with ground truth data. See https://github.com/weberdc/find_hccs for code and data.
Presented at ASONAM'20 (2020 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining).
Co-authored with Frank Neumann (University of Adelaide)
The Pessimistic Investor Sentiments Indicator in Social NetworksTELKOMNIKA JOURNAL
With the worldwide proliferation of social networks, the social networks have played an important role in the social activities .Peoples are inclined to obtain the corresponding public opinion to make decision such as shopping, education, investment and so on. Analysis of data generated by social networks has become an important field of research, however in the field of public opinion analysis of social networks the quantitative measure indexes are still lacking. In this paper, the calculation method of pessimistic investor sentiments indicator is proposed, and the index has a certain theoretical and practical value.
Information Use in Natural Habitats: A Comparative Study of Graduates in the ...Siobhán Dunne
Two librarians working with journalism students in higher education institutions in Ireland and Canada designed a comparative research study which surveyed graduates about the information resources they used to accomplish key communications tasks in their professional roles. The aim of the study was to (a) identify resources being used in practice and (b) harness that knowledge to improve both the content of information skills programmes and the pedagogical approach for teaching those skills. We were curious about the resources graduates actually used at work, both in traditional journalism positions and more broadly in other fields of communications.
An analysis of current professional journalism standards (Accrediting Council on Education in Journalism and Mass Communication 2012; National Council for the Training of Journalists 2012, 2014) and recent articles on information use by journalists (Machill & Bieller 2009; Wenger & Owens 2013) shows a disconnect between what journalists are expected to use and what they really use in daily practice. Literature on information literacy instruction for journalism students is quite descriptive about the resources we teach students in these programs but this is not always connected to what they might use in practice, in particular as they often have access to different resources than those provided by institutional subscriptions. Missing from the literature entirely is the consideration of journalists working in other communications roles.
Drawing on their prior work and other major studies, the authors will present recommendations for refining classroom practice to foster greater transfer of information literacy skills. We will present data from the survey and discuss the challenges the results present both in terms of what and how we teach in information literacy sessions for professional programs. Participants will be invited to complete a predictive version of the survey to compare what they think these professionals said with our results. This will be the basis for a discussion not only of our results, but also of our process, and how it might inform similar projects.
Although the focus of this study relates to employability skills in the field of journalism and communications, we will discuss the transferability of our findings and how our approach enables implications to be drawn for programmes that prepare students for future careers in other disciplines. Participants will be encouraged to generate questions they could use in similar surveys of graduates in other programs. Both librarians already work closely with faculty on existing journalism programmes; this paper will discuss how the insights gained from the study have been shared with colleagues to improve programmes for future students.
POLITICAL OPINION ANALYSIS IN SOCIAL NETWORKS: CASE OF TWITTER AND FACEBOOKIJwest
The 21st century has been characterized by an increased attention to social networks. Nowadays, going 24 hours without getting in touch with them in some way has become difficult. Facebook and Twitter, these social platforms are now part of everyday life. Thus, these social networks have become important sources to be aware of frequently discussed topics or public opinions on a current issue. A lot of people write messages about current events, give their opinion on any topic and discuss social issues more and more.
The official report off The Social Media And Governance Project, which I undertook for my finals at Birmingham City University.
It explored Nigeria's use of social media for the 2011 elections, and made a three pronged recommendation to the electorate, national electoral body, and individuals seeking various office.
The phenomenon of interest may be described as the extent to which social media may be used inpolitical campaigns, including past campaigns and future campaigns. This includes four main questions: (1) Was there significant use of social media in past political campaigns, namely the 2008 campaign of President Barack Obama? (2) Has social media continued to be used in subsequent political campaigns? (3) If social media has been used, have there been any problems with its use? (4) What is the best way to utilize social media in future political campaigns?
Group research project completed in the Spring Semester of 2016. Studied undergraduate students at Florida State University in order to gain knowledge on how they used social media platforms to gain information about the presidential election.
A method to evaluate the reliability of social media data for social network ...Derek Weber
In order to study the effects of Online Social Network (OSN) activity on real-world offline events, researchers need access to OSN data, the reliability of which has particular implications for social network analysis. This relates not only to the completeness of any collected dataset, but also to constructing meaningful social and information networks from them. In this multidisciplinary study, we consider the question of constructing traditional social networks from OSN data and then present a measurement case study showing how the reliability of OSN data affects social network analyses. To this end we developed a systematic comparison methodology, which we applied to two parallel datasets we collected from Twitter. We found considerable differences in datasets collected with different tools and that these variations significantly alter the results of subsequent analyses. Our results lead to a set of guidelines for researchers planning to collect online data streams to infer social networks.
Presented at ASONAM'20 (2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining)
Co-authors: Mehwish Nasim (Data61 / CSIRO), Lewis Mitchell (University of Adelaide), Lucia Falzon (University of Melbourne / DST Group)
Using Tweets for Understanding Public Opinion During U.S. Primaries and Predi...Monica Powell
Abstract
Using social media for political analysis, especially during elections, has become popular in the past few years where many researchers and media now use social media to understand the public opinion and current trends. In this paper, we investigate methods for using Twitter to analyze public opinion and to predict U.S. Presidential Primary Election results. We analyzed over 13 million tweets from February 2016 to April 2016 during the primary elections, and we looked at tweets that mentioned either Hillary Clin- ton, Bernie Sanders, Donald Trump or Ted Cruz. First, we use the methods of sentiment analysis, geospatial analysis, net- work analysis, and visualizations tools to examine public opinion on twitter. We then use the twitter data and analysis results to propose a prediction model for predicting primary election results. Our results highlight the feasibility of using social media to look at public opinion and predict election results.
Politics of tweeting, tweeting of politics: The uses of social media by state...Brenda Moon
Paper by Julia Schwanholz, Brenda Moon, Axel Bruns & Felix Münch Presentation presented at the 6th European Communications Conference - ECREA, Prague 2016
A web-based survey and theoretical research focuses mainly on the hazards that children are exposed to while surfing the digital world. It addresses the problem from parents/caregivers perspective and tries to shed light over the best ways of understanding and precautionary means. It is important for families to take all preventive measures to protect their kids from such hazards.
Social networking sites (SNSs) such as Facebook, Twitter and Google+ have attracted millions of users, many of whom have integrated those sites into their daily practices. As of this writing, there are hundreds of SNSs, with various technological affordances, supporting a wide range of interests and practices
Who’s in the Gang? Revealing Coordinating Communities in Social MediaDerek Weber
Political astroturfing and organised trolling are online malicious behaviours with significant real-world effects. Common approaches examining these phenomena focus on broad campaigns rather than the small groups responsible. To reveal networks of cooperating accounts, we propose a novel temporal window approach that relies on account interactions and metadata alone. It detects groups of accounts engaging in behaviours that, in concert, execute different goal-based strategies, which we describe. Our approach is validated against two relevant datasets with ground truth data. See https://github.com/weberdc/find_hccs for code and data.
Presented at ASONAM'20 (2020 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining).
Co-authored with Frank Neumann (University of Adelaide)
The Pessimistic Investor Sentiments Indicator in Social NetworksTELKOMNIKA JOURNAL
With the worldwide proliferation of social networks, the social networks have played an important role in the social activities .Peoples are inclined to obtain the corresponding public opinion to make decision such as shopping, education, investment and so on. Analysis of data generated by social networks has become an important field of research, however in the field of public opinion analysis of social networks the quantitative measure indexes are still lacking. In this paper, the calculation method of pessimistic investor sentiments indicator is proposed, and the index has a certain theoretical and practical value.
Information Use in Natural Habitats: A Comparative Study of Graduates in the ...Siobhán Dunne
Two librarians working with journalism students in higher education institutions in Ireland and Canada designed a comparative research study which surveyed graduates about the information resources they used to accomplish key communications tasks in their professional roles. The aim of the study was to (a) identify resources being used in practice and (b) harness that knowledge to improve both the content of information skills programmes and the pedagogical approach for teaching those skills. We were curious about the resources graduates actually used at work, both in traditional journalism positions and more broadly in other fields of communications.
An analysis of current professional journalism standards (Accrediting Council on Education in Journalism and Mass Communication 2012; National Council for the Training of Journalists 2012, 2014) and recent articles on information use by journalists (Machill & Bieller 2009; Wenger & Owens 2013) shows a disconnect between what journalists are expected to use and what they really use in daily practice. Literature on information literacy instruction for journalism students is quite descriptive about the resources we teach students in these programs but this is not always connected to what they might use in practice, in particular as they often have access to different resources than those provided by institutional subscriptions. Missing from the literature entirely is the consideration of journalists working in other communications roles.
Drawing on their prior work and other major studies, the authors will present recommendations for refining classroom practice to foster greater transfer of information literacy skills. We will present data from the survey and discuss the challenges the results present both in terms of what and how we teach in information literacy sessions for professional programs. Participants will be invited to complete a predictive version of the survey to compare what they think these professionals said with our results. This will be the basis for a discussion not only of our results, but also of our process, and how it might inform similar projects.
Although the focus of this study relates to employability skills in the field of journalism and communications, we will discuss the transferability of our findings and how our approach enables implications to be drawn for programmes that prepare students for future careers in other disciplines. Participants will be encouraged to generate questions they could use in similar surveys of graduates in other programs. Both librarians already work closely with faculty on existing journalism programmes; this paper will discuss how the insights gained from the study have been shared with colleagues to improve programmes for future students.
POLITICAL OPINION ANALYSIS IN SOCIAL NETWORKS: CASE OF TWITTER AND FACEBOOKIJwest
The 21st century has been characterized by an increased attention to social networks. Nowadays, going 24 hours without getting in touch with them in some way has become difficult. Facebook and Twitter, these social platforms are now part of everyday life. Thus, these social networks have become important sources to be aware of frequently discussed topics or public opinions on a current issue. A lot of people write messages about current events, give their opinion on any topic and discuss social issues more and more.
The official report off The Social Media And Governance Project, which I undertook for my finals at Birmingham City University.
It explored Nigeria's use of social media for the 2011 elections, and made a three pronged recommendation to the electorate, national electoral body, and individuals seeking various office.
The phenomenon of interest may be described as the extent to which social media may be used inpolitical campaigns, including past campaigns and future campaigns. This includes four main questions: (1) Was there significant use of social media in past political campaigns, namely the 2008 campaign of President Barack Obama? (2) Has social media continued to be used in subsequent political campaigns? (3) If social media has been used, have there been any problems with its use? (4) What is the best way to utilize social media in future political campaigns?
Group research project completed in the Spring Semester of 2016. Studied undergraduate students at Florida State University in order to gain knowledge on how they used social media platforms to gain information about the presidential election.
A method to evaluate the reliability of social media data for social network ...Derek Weber
In order to study the effects of Online Social Network (OSN) activity on real-world offline events, researchers need access to OSN data, the reliability of which has particular implications for social network analysis. This relates not only to the completeness of any collected dataset, but also to constructing meaningful social and information networks from them. In this multidisciplinary study, we consider the question of constructing traditional social networks from OSN data and then present a measurement case study showing how the reliability of OSN data affects social network analyses. To this end we developed a systematic comparison methodology, which we applied to two parallel datasets we collected from Twitter. We found considerable differences in datasets collected with different tools and that these variations significantly alter the results of subsequent analyses. Our results lead to a set of guidelines for researchers planning to collect online data streams to infer social networks.
Presented at ASONAM'20 (2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining)
Co-authors: Mehwish Nasim (Data61 / CSIRO), Lewis Mitchell (University of Adelaide), Lucia Falzon (University of Melbourne / DST Group)
Using Tweets for Understanding Public Opinion During U.S. Primaries and Predi...Monica Powell
Abstract
Using social media for political analysis, especially during elections, has become popular in the past few years where many researchers and media now use social media to understand the public opinion and current trends. In this paper, we investigate methods for using Twitter to analyze public opinion and to predict U.S. Presidential Primary Election results. We analyzed over 13 million tweets from February 2016 to April 2016 during the primary elections, and we looked at tweets that mentioned either Hillary Clin- ton, Bernie Sanders, Donald Trump or Ted Cruz. First, we use the methods of sentiment analysis, geospatial analysis, net- work analysis, and visualizations tools to examine public opinion on twitter. We then use the twitter data and analysis results to propose a prediction model for predicting primary election results. Our results highlight the feasibility of using social media to look at public opinion and predict election results.
Politics of tweeting, tweeting of politics: The uses of social media by state...Brenda Moon
Paper by Julia Schwanholz, Brenda Moon, Axel Bruns & Felix Münch Presentation presented at the 6th European Communications Conference - ECREA, Prague 2016
A web-based survey and theoretical research focuses mainly on the hazards that children are exposed to while surfing the digital world. It addresses the problem from parents/caregivers perspective and tries to shed light over the best ways of understanding and precautionary means. It is important for families to take all preventive measures to protect their kids from such hazards.
Social networking sites (SNSs) such as Facebook, Twitter and Google+ have attracted millions of users, many of whom have integrated those sites into their daily practices. As of this writing, there are hundreds of SNSs, with various technological affordances, supporting a wide range of interests and practices
Academic Research, part of MBA study in AAST. Consumer behavior subject.
The findings show that the selected sample of people are all social media users but the level of addicting the social media is differs from person to other. Furthermore, it shows that there is a significant positive relationship between social media addiction and different life dimensions destructions in the Egyptian society, in all manners such as the personal relations, work productivity, health and lifestyle. Accessibility and time spent on social media affects the degree of addiction and so the destruction as well.
marketingThe Effectiveness of social media in event Mr Nyak
marketingThe Effectiveness of social media in event marketingThe Effectiveness of social media in event marketing The Effectiveness of social media in event marketingThe Effectiveness of social media in event marketing The Effectiveness of social media in event marketing The Effectiveness of social media in event marketingThe Effectiveness of social media in event marketingThe Effectiveness of social media in event marketingThe Effectiveness of social media in event marketingThe Effectiveness of social media in event marketingThe Effectiveness of social media in event marketingThe Effectiveness of social media in event marketing The Effectiveness of social media in event marketingThe Effectiveness of social media in event marketingThe Effectiveness of social media in event marketingThe Effectiveness of social media in event marketingThe Effectiveness of social media in event marketing The Effectiveness of social media in event marketing The Effectiveness of social media in event marketingThe Effectiveness of social media in event marketing The Effectiveness of social media in event marketingThe Effectiveness of social media in event marketing The Effectiveness of social media in event marketingThe Effectiveness of social media in event marketing The Effectiveness of social media in event marketing The Effectiveness of social media in event marketing The Effectiveness of social media in event marketingThe Effectiveness of social media in event marketing The Effectiveness of social media in event marketingThe Effectiveness of social media in event marketing
Usman Koroma
Chapter 1 (4-5pages) Introduction From Assignment 01 include.docxtidwellveronique
Chapter 1 (4-5pages) Introduction: From Assignment 01 include:
1.1 Your business research topic. What is your topic and what is its business significance.
1.2 A brief background/literature discussion of your topic. Provide a list of research questions for the identified business problem or opportunity.
1.3 A brief description of the research methodologies and techniques to be used for the research project. What research methodology will you use?
1.4 A description of the research process. What will be the steps in your project?
1.5 Outline describing what will be in each chapter of the report.
Chapter 2 (8-12 pages)Literature Review: From Assignment 02 include:
2.1 Introduction to Literature Review: Start with introduction which includes a list of the topic you will do a literature review on, what your hypotheses are from these topics that you are starting out with.
2.2 Topic 1: Define your 1st key word or phrase. Provide strengths and weaknesses from literature about the topic. Provide at least 4 references. Analyse your hypothesis about this topic and discuss your conclusion.
2.3 Topic 2. Define your 2nd key word or phrase. Provide strengths and weaknesses from literature about the topic. Provide at least 4 references. Analyse your hypothesis about this topic and discuss your conclusion.
2.4 Topic 3: Define your 3rd key word or phrase. Provide strengths and weaknesses from literature about the topic. Provide at least 4 references. Analyse your hypothesis about this topic and discuss your conclusion.
2.5 Topic 4: Define your 4th word or phrase. Provide strengths and weaknesses from literature about the topic. Provide at least 4 references. Analyse your hypothesis about this topic and discuss your conclusion.
2.6 Conclusion to Literature Review
Enterprise adopting social network
1. Introduction to research topic
This proposal is about the use of social networking utilized by the modern business. Different approach in this article, a method and apparatus appears to be used for the implementation of successful future research.
It is assumed and believed that by the use of social network the modern business reach to success and social network is key element for getting success. There are so many business small or big both business use social network as a marketing device which became advantage for the success of business activities. Facebook and Twitter are the good example of social network and they are cheap, easy and can reliable as well. By the use of social network any business can build their image fame and goodwill and target product to final customer and show their different brands as well. So these networks are like opportunity to learn and develop information by which business know their customer and can get feedback. By making correct marketing intelligence and knowing competitor any business can make good bonding with their customers.
2. Specific Question
Problem faced in this context refers to the areas of the definition ...
Quiz 3.2 Outline FORMAT for JE 3Method 3 – Similarities and Diff.docxaudeleypearl
Quiz 3.2 Outline FORMAT for JE 3
Method 3 – Similarities and Differences
Instructions: Now that you have learned how to organize your writing, write an outline using the format below. This is the outline you will use in writing JE 4. Follow these instructions to submit your work:
1. On page 2 of this document, you have an outline format with text blocks you can populate with information. This information is the skeleton of your writing or of your OUTLINE. Be sure to use KEYWORDS and/or PHRASES. Remember that the purpose of an outline is to help you organize your material in a quick and efficient way before you spend time writing a document. The thesis statement is expected to be a complete sentence which includes the TOPIC, the CONTROLLING IDEA and the BRANCHES. The more material you include in your outline, the easier it will be for you to write your essay. You can make the text boxes bigger to include more text by clicking on the corner and dragging it down.
2. As soon as you complete all the areas that need to be populated with text, copy the outline as a Word document on to your computer memory. You do not need to include this page of instructions.
3. Go back to the quiz where you found this assignment and attach your OUTLINE. To do that, click on ATTACHMENTS. When the little ATTACHMENT window opens, look for the window that says BROWSE.
4. Look for the outline file that you just saved in your computer memory. By clicking on it, you will select it. When you will see your document in the BROWSE window, click on UPLOAD FILE and then click FINISHED.
5. Now your outline document is ready to be submitted from your drop box as an attachment.
6. Before you submit your outline, you will see a link for the RUBRIC which appears on this quiz’s drop box. Click on it to make sure you have covered all the aspects of your outline. This RUBRIC is the grading instrument that your professor will use to grade this quiz.
7. Finally, don’t forget to click SUBMIT. If you don’t, your work will not go through and you will not get a grade.
Thesis Statement (Establishing Similarities and Differences)
Main Idea for Developmental Paragraph 1 (Similarities)
Main Idea for Developmental Paragraph 2 (Differences)
Topic 1
Topic 2
Topic 3
Topic 4
Topic 5
Topic 6
Conclusion Statement
Public Administration and Information
Technology
Volume 10
Series Editor
Christopher G. Reddick
San Antonio, Texas, USA
[email protected]
More information about this series at http://www.springer.com/series/10796
[email protected]
Marijn Janssen • Maria A. Wimmer
Ameneh Deljoo
Editors
Policy Practice and Digital
Science
Integrating Complex Systems, Social
Simulation and Public Administration
in Policy Research
2123
[email protected]
Editors
Marijn Janssen Ameneh Deljoo
Faculty of Technology, Policy, and Faculty of Technology, Policy, and
Management Management
Delft University of Technology Delft University of Tec ...
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
2. 2
Table of Contents
1 THE PROJECT AND OBJECTIVES OF SURVEY ............................................................................ 3
2 METHODOLOGY.................................................................................................................... 3
2.1 Sample, schedule and tool ............................................................................................. 3
2.2 Adjustments.................................................................................................................. 4
2.3 Profile of the Respondents............................................................................................. 4
2.4 Limitations .................................................................................................................... 5
3 DATA ANALYSIS AND THE RESULTS........................................................................................ 5
3.1 Behavior towards Social Networks................................................................................. 5
3.2 Intermediate Summary for behavior towards social networks ...................................... 10
3.3 Habits of users towards the most important social networks ........................................ 10
3.4 Intermediate Summary for habits of users towards the most social networks ............... 14
3.5 Shared contents and applications................................................................................. 15
3.6 Intermediate summary for shared contents and applications........................................ 17
3.7 Cluster Analysis ........................................................................................................... 17
3.7.1 Methodology ................................................................................................................. 17
3.7.2 Cluster Analysis for opinions toward social networks................................................... 18
3.7.3 Cluster Analysis for motivations.................................................................................... 21
3.8 Potential Improvements for social networks ................................................................ 24
4 MANAGERIAL SUMMARY.................................................................................................... 25
5 RECOMMENDATIONS.......................................................................................................... 26
6 APPENDIX........................................................................................................................... 28
3. 3
1 THE PROJECT AND OBJECTIVES OF SURVEY
The European Master in Business Studies (EMBS) is a master degree in management with a focus on
marketing. This program is run by four different universities in various European countries (University
of Trento in ITALY, University of Savoie in FRANCE, University of Kassel in GERMANY and University of
León in SPAIN).
As part of the studies in “Marketing Research” in the University of Savoie, each year the EMBS
students work on a marketing research project about a specific topic. This year, EMBS students
decided to work on a project related to the online social networks.
Social networks are communities of individuals or organizations directly or indirectly linked, who are
gathered according to common interests, such as musical tastes, passions or professional life. On the
Internet, many websites are the source of creation of these networks, such as LinkedIn in the
professional world, or Facebook, MySpace for the general public. In addition, social networks are
becoming more and more popular every day, and more than 350 ones are commonly used around
the world.
Hence, the objective of this project is to analyze the behaviors of young people (between 15 and 30
years old) towards social networks in order to define their needs. Lastly, with the help of the key
findings of this research, the EMBS students would have to give recommendations for a new and
potential social network offering a new concept and new or better applications.
2 METHODOLOGY
To reach the above-mentioned goals, we firstly created an online survey in order to analyze the
behaviors, opinions and preferences of young people. In this survey we focused on three main
points: their behaviors towards the use of social networks, their opinions about the social networks
they mostly use, their motivations for using social networks.
After creating the online questionnaire1
in English, the EMBS students who come from six different
countries (France, Germany, Italy, Romania, Spain and Turkey) translated it into their mother
tongues.
2.1 Sample, schedule and tool
As the project aims at analyzing the behaviors towards social networks, we decided to address the
online questionnaire to young European people between 15 and 30 years old.
In order to get in contact with young Europeans and make them fill in our survey, the EMBS students
collected approximately 200 contacts per country, which could fit in this profile. Except from direct e-
mailing, we also used e-mail groups and social networks to reach as many young people as possible.
On 3rd of May 2010, the online questionnaire was sent out to all those contacts. During one week,
the EMBS students kept sending reminders in order to ask people to participate to this project.
Finally, on 12th
of May, we received 1095 answers out of the approximately 1500 contacts gathered
in the different countries. Then, we started to analyze the results of the survey, by using the Sphinx
Survey software.
The Sphinx Survey Software is professional statistic software which offers an easy all-in-one tool,
which would support the students in developing, conducting and analyzing the survey.
1
The questionnaire could be found in appendix
4. 4
2.2 Adjustments
In order to have more meaningful results which also correspond to the target, we decided, at the
beginning of the project, that we had to make some corrections on the results we got.
First of all, there were given answers which did not fit in the target group, concerning the age and the
country. As we decided to focus on six countries (France, Germany, Italy, Romania, Spain and Turkey)
and on people between 15 and 30 years old, we first deleted the answers from people coming from
other countries than the determined ones and the answers from people over 30 years old. So
regarding age, the variable named “30 and more” corresponds only to the people who are 30 years
old.
Secondly, we decided to deduct both systematic answers and the ones with extreme values that the
Sphinx Software detected, in order to reach more clean and reliable results.
Consequently, at the end of the data cleaning process, we only kept 892 answers which fit in our
objectives and target group.
Furthermore, since we got much more answers from Turkey, France and Germany than from the
three other countries; we thought that the results did not represent the actual characteristics of each
country. That is why we decided to weight the countries according to the size of their population.
Nevertheless, we avoided to weight the data according to other characteristics of the countries (e.g.
internet usage, age etc.) due to the concerns about data manipulation. Below, you can find the table
of weighting for each country constituted by the previous figures and the new adjustments.
2.3 Profile of the Respondents
After having made the necessary adjustments, we drew a profile of our final sample.
Concerning the main characteristics of the respondents, due to the result of the survey, we can
affirm that a big percentage of respondents is represented by young female students between 24
and 29 years old who declared that they are not in a relationship.
Moreover, as we already mentioned in the adjustment part, most of the respondents are from
Germany, France and Turkey. Concerning the Internet knowledge, a big number of the participants
has an advance or good level.
5. 5
2.4 Limitations
Lack of representativeness of the analysed sample:
Answers of the respondents influenced by the fact that we sent out
the questionnaire via e-mails and social networks.
Due to the big difference in the number of answers collected for each of the six different
countries.
To address this problem: weighting of the sample according to the size of the population of
each country.
Most of the respondents are either students or workers; this means that we do not have
a lot of information about the other types of occupations.
Lack of representativeness of the answers regarding the most important social network
Indeed, most of the respondents mentioned Facebook as the most important social network
for them, so the major part of the answers given in the questionnaire refers to Facebook.
Consequently, there is a lack of information about the other social networks.
Chosen sample: people between 15 and 30 years old, which is a sample already targeted by
the existing social networks.
Difficulties to address recommendations for a brand new social network with a new concept
as the information we gathered are consequently limited.
An eventual missing question about the level of education of the respondents
Could have generated interesting information
3 DATA ANALYSIS AND THE RESULTS
3.1 Behavior towards Social Networks
In this section we will cross several questions in order to find different patterns and behaviors
regarding the social networks users. This analysis will help us getting a deeper knowledge on how
users act according to their different personal characteristics.
Use / no use of social networks
We will begin this study by analyzing the first question about the respondents’ use of social
networks. This question will be successively crossed with others ones.
Use / no use vs. countries
Almost all the countries present a similar distribution, starting from 98% of use for the French
respondents to 93% for the Spanish ones. The only country which does not present figures in
accordance to the others is Romania with 85%. It could be assumed that this may be a result of the
development of the Internet connection or maybe due to the popularity of social networks in
Romania.
6. 6
Use / no use vs. Marital Status
There are no significant differences among the different marital status. The lowest percentage
concerns the married users (91%). Then, we can assume that the use of social networks is a rather
personal activity as, most of the time, after getting married the social life can be reduced. 2
Use / no use vs. Age
There is a similar distribution across the different age ranges. In the “Less than 18 years old” range,
there is a positive specificity, since 17% of them do not use social networks, which is significantly
higher than the average. The rest of the age ranges present a use of social networks between 95%
and 97%3
Various social networks
After that, we analyzed the question about the different social networks that are used by the
respondents. First of all, due to the huge number of options given in the questionnaire, we decided
to remove the websites which seemed to be less important and we worked on a limited table
including the six most important websites (Facebook, StudiVZ, Twitter, MySpace, LinkedIn, Tuenti).
We can see that Facebook was the most mentioned social network in the six countries (90% of the
users). Then, we found, on the one hand, more specific international websites such as Twitter and
MySpace and, on the other hand, national ones such as StudiVZ (German social network) and Tuenti
(Spanish one). 4
Social networks vs. Countries
Thanks to this study, we can see how Facebook is well-known across the different countries;
Facebook is less representative in Germany (negative specificity) as StudiVZ seems to be the most
used social network in that country (positive specificity). We can also see that the national websites
such as StudiVZ and Tuenti have no real success out of their home countries. Moreover, it is also
interesting to highlight the presence of LinkedIn (professional social network) and Twitter in Turkey.
2
Please see the “Use/No use X Marital Status” graph in the appendix
3
Please see the “Use/No use X Marital status” graph in the appendix
4
Please see the “ Used SN” graph in the appendix
7. 7
Most important social networks
In this question, users can select more than one option so we do not know what the distribution of
this usage is. To avoid that, we will focus on a question regarding the mainly used social networks.
Main social networks vs. Countries
Facebook is the mainly used social network in all the countries except in those which have a well
developed national social network such as Germany with StudiVZ (57% of the German users prefer
using it instead of Facebook). As we previously said, Turkey is the country in which Twitter (7%) and
LinkedIn (7%) are among the most popular SNs.
Main social networks vs. Age
Facebook is the mainly used social network within all the age ranges (69% of those between 24 to 26
and 86% of the ones under 18 and from 18 to 20). We can see that LinkedIn presents higher
percentages in the age range in which people tend to finish their studies and are looking for a job
(people from 24 to 26 (2%) and from 27 to 29 (7%).5
Main social networks vs. Occupation
As the target of our survey is people between 15 and 30 years old, most of them are students. It is
interesting to highlight the fact that the most important social network for workers is LinkedIn (69%)
but not for those who are looking for a job (11%).6
5
Please see the “Most important SN X Age” graph in the appendix
6
Please see the “Most important SN X Occupation” graph in the appendix
8. 8
Main social networks vs. Marital Status
Most of the respondents are either single people (55%) or people in a relationship (41%). Among the
different social networks, Tuenti is the one which gathers the highest percentage of single people
(64%) and LinkedIn presents the highest percentage of married people (15%) as it is mainly used by
professional (oldest age ranges). 7
Main social networks vs. Level of Internet
Everybody has, at least, an intermediate level of Internet and most of the people consider they have
an advanced (38%) or a good level (35%). It is interesting to stress that the highest percentage of
expert users is found within LinkedIn users (40%), the reason is probably that LinkedIn is a
professional social network.8
After analyzing the main social networks used by the respondents, we can say that social networks
are mainly considered as a social activity and try to reach as many users as possible.
Reasons for not using social networks
As far as the very first question is concerned, those who answered that they do not use social
networks had to answer to another question in order for us to understand the reasons of their
reluctance.
Reasons for not using social networks vs. Age
The respondents who are not found of social networks, all have different reasons for not using them.
Regarding the age, we can see that people who rarely use the Internet have less than 18 years old.
This is maybe due to the fact that, as they are young, they are not allowed to freely use the Internet.
A lot of other reasons such as the lack of interest, time or privacy, are mainly given by people aged
between 24 and 26. Those who find them useless mainly have between 21 and 23 years old.
Reasons for not using social networks vs. Occupations
According to their occupation, people can have different reasons for not using social networks.
All of those who use the Internet in a seldom way seem to be either studying or going to school
(linked to the fact that they have less than 18 years old).9
7
Please see the “Main SN X Marital Status” graph in the appendix
8
Please see the “Main SNs X Level of internet” graph in the appendix
9
Please see “Reasons for not using social networks” graph in the appendix
9. 9
Reasons for not using social networks vs. countries
In the above-presented graph, we chose to analyze the different reasons why people do not use
social networks according to the country in which they live.
Those who are not interested in social networks are mostly represented by Romanian people
because this practice is not really popular in Romania.
The people who mainly answered that they do not have time and that they think social networks are
of no use are mainly Turkish.
German respondents are the ones who mostly answered they do not want to develop virtual
relationships.
Eventually, approximately 70% of the persons who almost do not use Internet are Italian.
Level of Internet
Level of Internet vs. Countries
In this graph, we wanted to get a deeper knowledge on the level of Internet of the participants in the
six different countries.
The general trend is that, in all the analyzed countries, the respondents have a quite high level of
Internet.
Indeed, in France, Italy and Romania, there are mostly people with a good level of Internet. In
Germany and in Turkey, people described themselves as users with an advanced level.
Spanish respondents have a good to advanced level of Internet.
We have to highlight that none of the respondents seem to have a low command of the Internet.
10. 10
3.2 Intermediate Summary for behavior towards social networks
Considering the countries, Romanian people tend to use SNs less than the other countries. It
could be due to Internet connection issues or maybe to the fact that SNs are not so popular
in Romania.
Facebook is the most extended and popular SN in the world. Except from Facebook there are
several SNs used commonly but most of them are national ones (e.g. StudiVZ for Germany
and Tuenti for Spain) or specialized on particular target groups (e.g. LinkedIn for
professionals).
People under 18 years old who are not using social networks mainly said that it is because
they rarely use the Internet; maybe because they cannot use it freely.
In the six different countries, the major part of the respondents has a high Internet
knowledge.
3.3 Habits of users towards the most important social networks
In the second part of our survey, we aimed at going a little bit further into details on the online social
networks that the respondents mostly use.
Frequency of use
Now, we will analyze the frequency of access to
social networks. We can see that, most of users
answered that they log into their main social
network several times a day (62%) or once a day
(20%). So, we can consider that most of the users
are enthusiastic or even addicted users.
Frequency vs. Countries
Romanian users (35%) log in less often than the users from the other countries, maybe because they
cannot access Internet as easily as the other ones. The case of Germany is interesting since they have
a very well developed Internet system. 49% of them answered that they access social networks
several times a day.10
Frequency vs. Occupation
People who are working (51% “Several times a day”) log into social networks less often than people
who are studying (66% “Several times a day”). This may be because workers have less free time after
working.11
Frequency vs. Main social networks
Social networks for social activities such as Facebook (69% in “Several times a day”) and Tuenti (85%
in “Several times a day”) are more often visited by their users than specific or professional social
networks like StudiVZ (38% in “Several times a day”) or LinkedIn ( 36% in “Several times a day”).12
The frequency of connection to social networks may be related to the possibility users have to access
Internet and also to the kind of social networks or to the reasons why they use them.
10
Please see the “Frequence of use X Countries” graph in the appendix
11
Please see the “Frequency of use X Occupation” graph in the appendix
12
Please see the “Frequency of use X Main social networks” graph in the appendix
11. 11
Number of contacts
As we take the number of contacts into account, we see that there are no significant differences
concerning all the demographics of the respondents. Most of the respondents have around 101 -250
(by 41 %) and 251 - 500 (by 25%) contacts.13
Number of contacts vs. Age
There is one demographic factor which should be taken into consideration and shows different
trends: age groups. Compared with the other age groups, there is a big tendency to have more
contacts (between 250 and 500) among the people in age up to 20.
When we combine this result with the motivations to use the social networks part of the survey, we
see that the respondents younger than 18 are dominantly using the social networks to make new
friends.14
Location to access
We also wanted to analyze the places where the
respondents mostly connect to social networks.
Results showed us most of respondents connect
firstly from their home, then from their place of study
and work place.
The second place of access is the place of study, due
to the fact that, most of respondents are students.
Indeed, many high schools and universities currently
provide an Internet access to their students.
Location to access vs. Country
Moreover, when we analyzed the results for this question country by country, we saw that French,
Italian, German and Spanish respondents access to social networks firstly from home and then from
the place of study, while Turkish and Romanian people prefer to access firstly from home and then
from their work place.15
Location to access vs. Occupation
The location to access is also depending on the occupation of the respondents. Results show us that
after the “home”, the respondents who have a job, mostly connect to social networks from their
13
Plase see the “Number of contacts” graph in the appendix
14
Please see the” Age X Motivation of making new friends” graph in the appendix
15
Please see the “Locations to access X Country” graph in the appendix
12. 12
workplace while students (mostly between 18 and 23 years old - university students) access from
place of study.16
Motivation to use the social networks
Another goal we try to figure out in this section was
the motivations of using the social networks. In
general, social networks are used mostly for
personal reasons, 83% of our respondents expressed
that they are using the social networks for personal
motivations. Since nearly 3% of respondents
answered that they use them for professional motivations, we might suppose that the social
networks, which have professional concept, are still not so popular among the young people.
Moreover only 15% of respondents said that they use the social networks for both personal and
professional reasons.
Motivations to use vs. social networks used
When we take into consideration the top 6 social networks which are commonly used, we see that
the respondents tend to use social networks such as Facebook,StudiVZ,Tuenti mostly for personal
motivations. Moreover social networks like LinkedIN, which is a totally professional one, and Twitter
are used for professional motivations.
Motivations to use vs. Important social networks
The difference between personal and professional
motivations is even bigger when we look at the results
of the most important social networks. Hence, we can
say that people who use social networks are aware of
the concept and use them consciously.
Motivation to use vs. Age
There is no big difference about motivations of use concerning the age, the respondents pointed out
that they use social networks mostly with personal motivations. But, as we already mentioned in the
first section (“Main social networks vs. Age”), the social networks with professional perspective are
16
Please see the “Locations to access X Occupation” graph in the appendix
13. 13
mostly used by young people aged between 24 and 29; so linked with this data, the proportion of
professional use is bigger in these ages than other age ranges.17
Motivations to use vs. Occupation
When we analyze the motivations together with occupation, there is not significant variance
between the groups ( studying,working, working and studying, not working ) except for the increase
of professional use in the groups of studying and/or working people.18
Motivations to use vs. Countries
Concerning the countries, the percentage of people who answered that they are using the social
networks with personal and professional motivations are significantly bigger in Romania (38%) and
Turkey (32%) than in other countries.
Type of users
As far as users are regarded, most of the respondents answered that they are active when using
social networks.
It means that they use the provided contents as well as the applications quite a lot.
Type of users vs. age
Concerning the age, the most active users seem to be those under 18 years old and those aged 30.
The reason could partly be that, all the new ways of virtual communication are really famous among
the youngest.
The age range in which the most passive users can be found is the one composed by people between
24 to 26 years old.
17
Please see the “Age X Motivations” graph in the appendix
18
Please see the “Occupation X Motivation” in the appendix
14. 14
Type of users vs. Level of Internet
Now that we know that most of the respondents tend to be quite active when using social networks,
we can compare these data with their level of Internet.
We can easily notice that the use of social networks is directly linked to the competence of the users
regarding Internet.
Indeed, the higher their level of Internet, the more active they are.
Type of users vs. Level of satisfaction
Concerning the users, we found out that the way of using social networks is directly related to their
level of satisfaction.
Indeed, we can see that the more the respondents are satisfied by social networks, the more active
they are when using them.
For example, among the persons who gave a grade of 1 to the social network they regard as the most
important, only about 33% are active.
At the contrary, among the ones who gave 10 to the most important social network, 85% are active
when using it.
3.4 Intermediate Summary for habits of users towards the most social networks
The results show that most of the respondents access SNs several times a day. Furthermore,
we can assume that people who often access SNs may have a better Internet connection
and/or several ways of accessing the internet (e.g. Wi-Fi, Smart phones etc.).
Students tend to access SNs more frequently than people who work.
Most of the respondents pointed out that they have 101-250 contacts in the social networks
they use. On the other hand, young people under 20 tend to have even more contacts
compared with other ages.
15. 15
Results show that a big percentage of respondents access social networks from their home.
As a second place, they tend to access from place of study or work, depending on their
occupation.
Most of respondents are using the social networks for personal motivations. Plus, we see
that social network users are conscious of the concept of the SN they use, since the
professional motivations are increasing on the SNs which have professional concept such as
LinkedIn (especially for the respondents who are working and have between 24 and 29).
Most active users are found among those under 18 and the ones over 30.
The higher the Internet knowledge of the users is, the more active they are.
The higher the satisfaction of the users is, the more active they are when using social
networks.
3.5 Shared contents and applications
Shared contents
As we would like to figure out the tendencies of young people
concerning the online social networks, analyzing the shared
contents was crucial. The results showed us that the most
preferred contents to share are photos, and then it is
successively followed by text, links, videos and music.
Since the social networks are still not well-developed in music
sharing, the percentage of music shared through the online
social networks are still lower than other contents. 19
But on
the other hand, the music sharing rate is increasing when the
level of Internet knowledge increase.20
Concerning the age of the respondents, we could not see any significant difference between the
shared contents, except from the increase on the percentage for the music shared by the people who
are younger than 18. 21
Kind of used applications
Used applications vs. Countries
As far as the applications are concerned, a cross-table was used to link them to the six different
countries analyzed throughout this study.
19
You can find the opinions of respondents about music sharing in the last section called “What else?”
20
Please see the “Shared content X Level of Internet knowledge “ graph in the appendix
21
Please see the “Age X Shared content” graph in the appendix
16. 16
Here we can notice that, generally, in almost every country, the applications which are the most used
by people are “private messages” and “photos”.
The “chat” is also used a lot in most of the countries except for Turkish people who seem to use it a
bit less than the other participants. We can assume that the latter prefer to use other programs such
as Msn Messenger to chat.
“Videos” and “music” are a bit less used by almost all the respondents than the other applications.
However, Turkish people use “videos” a lot. This could be explained by the fact that, some of the
video websites such as YouTube are forbidden in Turkey.
We can also see that, the least used application in all the countries is “music”, apart for Turkey where
it is used approximately as often as the “chat”.
Used applications vs. Age
The used applications can also vary according to the age of the users.
“Private messages” is the application which is used the most often by all the different age ranges.
Nevertheless, people under 18 years old use them slightly less than the other ones.
The second mostly used application is “photos” and this can be applied to all the respondents, no
matter their age.
Then, we can see that the older the respondents, the less they use the “chat”.
We can think that the eldest ones may not be really keen on virtual communication.
“Games” and “Music” applications are mainly used by the youngest respondents and by the people
aged 30.
Used applications vs. Most important social networks
This analysis shows that the applications used vary widely depending on the social networks.
17. 17
As far as Facebook is concerned, the two mostly used applications are “private messages” and
“photos”. The same trend can be noticed for Tuenti and Twitter.
Concerning StudiVZ, “private messages” is, by far, the application the respondents most often use.
Regarding LinkedIn, the situation is different. “Private messages” account for more than 50% of the
used applications, and the other ones are not widely spread. This can be explained by the fact that
LinkedIn is a social network used to build professional relationships; consequently, it is used for more
serious reasons than the other ones.
We can also see that MySpace is used a lot for “photos” and “videos”. One thing that has to be
stressed is that, this social network is also used a lot for “music”, contrary to the other ones. This can
be explained by the fact that it is the only one which offers this option.
3.6 Intermediate summary for shared contents and applications
Considering the shared contents, photos and texts are the most popular ones. In addition to
that, people would like to share more music through social networks.
Mostly used applications in the different countries are “private messages” and “photos”
without any difference among the age ranges.
Turkish people do not use “chat” a lot as they may use other programs (e.g. Msn Messenger)
and also they tend to use more the “videos” probably because websites such as YouTube are
forbidden.
The older the respondents, the less they use the “chat”
As LinkedIn is a professional network, the mainly used applications is “private messages”
while MySpace is mostly used for music, as it is one of the most popular social networks that
offers this option.
3.7 Cluster Analysis
In the following part, we will deal with the two cluster analyses we created about the opinions of the
users on social networks and their motivations to use them.
3.7.1 Methodology
To begin with, we decided to use the same method for the two different cluster analyses.
First of all, we used a Principal Component Analysis (PCA) in order to manually define the number of
segments we will use and their characteristics.
We consequently used 9 variables for the clustering about the users’ opinions on social networks and
14 variables for the clustering linked with their motivations. They were both carried out in order to
understand what people think about the existing social networks and the reasons why they use
them.
After having done a map by using the mentioned variables, we gave names to the axes of each
clustering.
Regarding the opinions, we called the horizontal axis “risky”. In this one the positive values represent
the highest risks perceived and the negative values represented the lowest ones. The vertical axis
was named “utility” as the positive values mean that users think that social networks have a high
utility and the negative ones mean low utility to users. 22
The same process was conducted for the question of motivations; we called the horizontal axis
“interest to use SN”. It means the responses in the positive part represent highest interest in social
22
Please see “Manual Clustering (Q15-Q23)” in the appendix.
18. 18
networks and the ones in negative part represent lowest interest in using social networks. Lastly, we
named the vertical axis “personal motivations to use” which means that people in positive part, use
SNs for mostly personal reasons while the respondents in the negative part use the SNs for mostly
professional reasons.
For the first cluster analysis, we came out with four interesting segments, and according to the
variables they were referring to, we named them as: Enthusiastic, conscious, uninterested, and
defensive.
As far as the second clustering is concerned, we defined five segments which are: Sociable, curious,
expressive, serious, and trend followers.
After defining the clusters manually, we also used the automatic clustering made by the Sphinx
software to compare their level of significance. Since we crossed both automatic and manual clusters
with variables, we applied the Fisher test for both of them.
The best option is the one which has an:
Inter-variance as high as possible (as heterogeneous as possible between the groups)
Intra-variance as low as possible (as homogeneous as possible within the groups)
For the cluster which regards the opinions, as a result of F-test, we came out with a result of 1035.22
for the manual clustering while automatic one was 1463,12 .
For the motivations cluster, as a result of F-test, we came out with a result of 1218.2 for the manual
clustering while automatic one was 1407,95 .
So in the end we figured out that it would be more significant and reliable to analyze the data with
the help of the automatic classification.
3.7.2 Cluster Analysis for opinions toward social networks
Thanks both to the PCA and the automatic classification, we managed
to define four different segments to analyze:
Conscious users: high risk perceived and high utility
Defensive users: high risk perceived and low utility
Enthusiastic users: low risk perceived and high utility
Uninterested users: low risk perceived and low utility
The results show that, regarding their opinion about social networks, most of the people are
defensive users (32%); the second highest represented group is formed by the conscious users (29%).
These two segments believe that social networks have potential risks; however, conscious users have
a positive attitude towards the utility of these websites. On the other hand, defensive users have a
negative opinion of social networks.
The third group is formed by the enthusiastic users, who are eager to use social networks. They think
that they are useful tools and do not perceive them as risky (privacy, security, fake dimension). This
group represents one of the main targets of social networks.
The less represented segment is composed by the uninterested users, who are quite passive in the
sense that they neither see the utility of social networks nor their harmful side. Nevertheless, they do
not have a critical opinion about social networks.
19. 19
The most important segment for social networks is the one of the enthusiastic users since they
already are using them in an extensive way without having a bad opinion of their risks.
According to the conscious and defensive users, social networks need to be improved especially in
security.
Uninterested users represent the main challenge for social networks. Indeed, the websites would
have to offer new contents and services in order to interest them more with the same or increased
level of security. So we can consider this cluster as the main opportunity for the development of
social networks as it is a group which is still unknown and unexploited.23
23
For more detailed cross analysis, please see the “Cluster analysis for opinions” part in the appendix
20. Clusters Opinion Activities Expectation
s
Socio-
demographics
+ -
Conscious
- Popular
- User
friendly
- Dangerous
for privacy
- Voyeuristic
- Exhibitionist
ic
Contents: photos,
texts
Applications:
private messages,
chat, videos
- Increase
security
- Develop
privacy
options
- Under 18 and
more than 27
- Workers and
Students/Workers
- Italians, Spanish
Enthusiastic
- Popular
- Useful
- Trendy
- Time
consuming
- Voyeuristic
- Danger for
privacy
Contents: photos,
texts, links
Applications:
private messages,
chat, games
- Not remove
the already
existing
applications
- Develop new
applications
- From 21 to 26
- Non workers and
job seekers
- Germans,
Romanians
Defensive
- Popular
- Trendy
- Time
consuming
- Dangerous
for privacy
- Voyeuristic
Contents: photos,
links, text, videos
Applications:
private messages,
chat
- Develop new
applications
and tools
- Increase
security and
privacy
- From 18 to 23
- Students, workers
and non workers
- French, Turkish
Uninterested
- Useful
- User
friendly
n/a Contents: Photos,
tests
Applications:
private messages,
chat
- Get their
attention and
interest
- Develop new
fields
- Less than 18 and
people of 30
- Workers and job
seekers
- Germans, Turkish,
Romanians
21. 21
3.7.3 Cluster Analysis for motivations
As a result of cluster analysis, we defined five main classes, which are:
sociable people, expressive people, serious people, trend followers and
curious people.24
Description of each group:
Curious people: According to our analysis, “curious people” is the biggest class by 36%. In this class,
the people, who want to know what is happening in others’ life, are represented. They use social
networks mostly to find old friends and stay in contact with many people and get information about
other people to stay updated about their lives.
Sociable people: As it can be understood from the class name, they are people who would like to
contact as much people as possible. Results showed us that sociable people are the ones who enjoy
almost all ways of using social networks. Even if they give a big importance to networking, staying
updated about others’ lives and having fun, they also would like to express themselves through social
networks.
Trend followers: After our analysis, we figured out that, there are people who register to social
networks only because they do not want to get behind of new trends. They seem to be members of
social networks; but in reality, they do not show any interest in using it. The trend followers are
represented in overall classes by 17%.
Serious people: This class includes the people who use the social networks for mostly professional
motivations. In other words, professional users are eager to discover new contents and information.
The main difference, comparing with other classes, is that besides personal motivations, they are
using social networks also to promote an organization, a person or a group. They are presented by
14% in overall classes.
Expressive people: This class forms the 5% of all respondents. The main motivations of “expressive”
people are to share their ideas, feelings by expressing themselves through social networks and to
communicate a positive image to the public.
24For more detailed cross analysis, please see the “Cluster Analysis for Motivations” graphs in the appendix
23. 23
25
Youngest: 15 to 20; Middle-aged: 20 to 25; Oldest: 25 to 30
Cluste
rs
Motivations Age Occupation Country
+ -
Sociable
- Find old friends,
- Stay updated
-Find information
about someone
- Be in contact with
many people,
- Having fun
n/a Middle-aged
to oldest
25
- Studying and
working
Curious
- Stay updated
- Find old friends
- Discover new
content
- Show what I like,
my preferences
- Communicate a
positive image
- Express my
personality
Youngest to
middle-aged
- Looking for a job
- Studying/Going
to school
Expressive
- Show what I like,
my preferences
- Express my
personality
-Stay updated
- Find old friends
Youngest - Not working
- Looking for a job
Serious
- For professional
motives
- Promotion
- Discover new
content
- Having fun
- Stay updated
-Share feelings
- Dating
Middle-aged - Not working
- Studying and
working
Trend
followers
n/a - Be in contact with
many people
- Find old friends
- Having fun
- Stay updated
Middle-aged
to oldest
- Not working
24. 24
3.8 Potential Improvements for social networks
Lastly, we also would like to know the
respondents’ opinion about what else can be
improved or developed concerning social
networks. As you can see on the right, the
most important topics which should be
improved are: security, privacy, chat option,
and number of advertisements in the social
network.26
Security & Privacy: They are the most important concerns about social networks for respondents.
Most of the respondents mentioned that the social networks have security problems. Concerning the
privacy issue, they complain about data tracking and storage which means that the social networks
keep the information about them, even if they delete their accounts. Moreover, the respondents
would like to have different confidentiality options for the contacts they have. So that they can
define the level of “attainable” information about themselves for each contact or group.
Improvement of chat: Since the chat is a relatively new option in the social networks, the
respondents wish for some improvements on that option such as video conversation. They would like
to use the social networks to communicate with each other as much as sharing photos, videos, etc.
Less advertisement: This is one of the things which respondents mostly asked for. They pointed out
that the social networks have too many advertisements and the number of advertisements should be
reduced. Otherwise they suggest adding a blocking option for advertisements.
Customization of profile and layout: Some of the respondents emphasized that the layout of the
social networks is not satisfactory and even sometimes imitating each other. As young people would
like to be different or express themselves through their profiles, they would like to customize their
own layout or even to create new layouts.
Other ideas:
Some of the respondents mentioned that they receive too many sharings, so they would like
to have an option to group these sharings.
Better control (for harmful contents, fake profiles, etc.) and customer service
Data storage option for files
More music sharing and improvements of games
26
Please see the appendix for more detailed table
25. 25
4 MANAGERIAL SUMMARY
Considering the countries, Romanian people tend to use SN less than the other countries. It
could be due to the internet connection issues or maybe to the fact that social networks are
not so popular in Romania.
Facebook is the most extended and popular SN in the world. Except from Facebook there are
several SNs used commonly. But most of them are national ones (e.g. StudiVZ for Germany
and Tuenti for Spain) or specialized on particular target groups (e.g. LinkedIn for
professionals).
The results show that most of the respondents access to SN several times a day.Furthermore,
we can assume that people who often access SNs may have a better internet connection
and/or several ways of accessing the Internet (e.g. Wi-Fi, Smart phones etc.).
Students tend to access SNs more frequently than people who work.
Most of the respondents are using the social networks for personal motivations. Plus, we see
that social network users are conscious about the concept of SN they use, since the
professional motivations are increasing on the SNs which have professional concept such as
LinkedIn (especially for the respondents who are working and have between 24 and 29).
Considering the shared contents, photos and texts are the most popular ones. In addition to
that people would like to share more music through social networks.
Mostly used applications in the different countries are “private messages” and “photos”
without any difference among the age ranges.
Most active users are found among those under 18 and the ones over 30.
The higher Internet knowledge of the users is the more active they are.
The higher the satisfaction of the users is, the more active they are when using social
networks.
Concerning about necessary improvements, the participants highlighted 4 main ideas which
are security, privacy, chat option, and number of advertisements in the social network.
26. 26
5 RECOMMENDATIONS
The target group we chose to focus on when designing this prototype of social
network is constituted by students and young workers between 20 and 35 years old
who are curious, who like to try new things, and who are not reluctant to change. It
would allow a good promotion and advertising through word-of-mouth.
When designing a brand new social network, it is crucial to pay attention to the
already existing social networks as well as to the potentially new competitors.
Indeed, it is essential not to set up an already existing concept or to focus on a target
group that is already well addressed by another social network.
A good opportunity would be to create a social network devoted to the sociable,
curious and expressive users. This one would be a combination of blogs and social
networks such as Facebook. It would provide the users with the possibility to be in
contact with many people, to find old friends and to express themselves through
articles published on profiles.
A good idea would also be to pay more attention to the countries in which social
networks are the less popular, such as, for instance Romania. Indeed, it may be
better to draw a social network with a national focus in order to better address their
needs and expectations.
A trap that the new social networks designers would have to avoid is not to create a
copy of already existing websites such as Facebook. They have to offer a new
concept, new ideas and new contents (sport, music, etc.)
It is also important to get a deeper knowledge on country specificities and trends for
having more chance and opportunity in this sector.
Another suggestion is to set up a social network providing users with an all-in-one
account gathering two different profiles (personal and professional).
This new social network could also be a combination of Facebook and MySpace, that
is to say a website allowing to find old friends, to be in contact with many persons
and to share music with them.
Even if most of the popular social networks have a chat option, it is newly developed.
So some improvements or new features such as multi-chat (chatting with several
persons in the same conversation) and video conference could create a great
comparative advantage among the competitors.
Since the young people ask for new and more applications to use in their social
networks, well-developed and attractive applications especially in music sharing and
games would help to improve the popularity of new social networks.
As we mentioned in the report, the privacy and security are still big problems for
social networks. Especially the security should be risen to the maximum level by
controlling harmful contents, applications, etc.
27. 27
Data tracking should be decreased since it is one of the common reasons for not
using social networks or deleting their accounts. In addition to do that, a social
network should always be ready to help their users immediately in case of problems
in the website.
Social network users would like to be “owner” of their accounts, which means that
they should manage the settings. As balancing everybody’s demand about privacy
settings at the same level is hard, there should be different levels for privacy settings
which they could choose; or even, let them choose different confidentiality levels for
different contacts would surely increase the satisfaction of users.
One of the main financial sources of social networks is online advertisements. But the
number of advertisements in the page should be carefully defined since it can
sometimes deter people from using social networks. Even if we cannot discard this
financial source, we can let users take the decision of receiving advertisements but,
at the same time, we should provoke them to receive more ads with special offers
and promotions.
Concerning the sharings, the new social network should improve the quality of
sharing and satisfaction by letting the users group them. Related to this topic, the
users could be able to store data (video, music, presentations, word documents,
spreadsheets etc.) in the social network.
One golden opportunity for a new social network would be the customizable layout
for their own profiles as the young people would like to be more expressive and
different in every part of life.
AN ALTERNATIVE IDEA FOR A NEW SOCIAL NETWORK
According to some sources, an expanding target group for social networks is made of
older generations especially for people between 40-50 years old, as they seem to be
more and more interested in them. Consequently, working on this niche would be
another alternative. 27
27
http://edition.cnn.com/2009/TECH/04/13/social.network.older/index.html
39. 39
6.4 Cluster Analysis for opinions about Social Networks
Manual Clustering Q15-Q23
Utility (+)
Utility (-)
Risk (high)Risk (low)
SN: Useful
SN: Trendy
SN: Widespread / Popular
SN: Fake
SN: Voyeuristic
SN: Exhibitionistic
SN: Dangerous for privacy
SN: Time consuming
SN: User friendly
Defensives
Enthusiastics
Conscious
Uninterested
40. 40
Cross Analysis for Opinions
Classes for Opinions vs. Countries
We can identify several differences across countries. France has the largest percentage of defensive
users (66%) and the second smallest percentage of uninterested users (7%). Germany has the most
41. 41
regular distribution with a huge number of enthusiastic users (35%). Spain has the largest number of
conscious users (57%) and the lowest number of uninterested ones (1%). Italy has the lowest number
of defensive users (14%) and a quite big number of conscious users (47%). Uninterested users (23%)
are mainly gathered in Romania, which could be a good opportunity to establish a new social
network there. Furthermore, it is important to highlight that there are no conscious users in
Romania. Turkey presents a low number of enthusiastic users (10%) since the defensive people are
more dominant (37%)
It could be interesting to focus on those countries which have either a large number of uninterested
users (Romania, Germany or Turkey) or a small number of enthusiastic users (Turkey or Spain).
Classes for Opinions vs. Age
We must stress that the youngest users (under 18) have a
very high percentage of uninterested users (44%) and the
lowest number of enthusiastic users (5%). We can think that
the younger users are either not concerned about social
networks or do not think that the current social networks
meet their needs and tastes. This point also offers a wide
range of possibilities regarding new websites specialized for
teenagers.
Classes for Opinions vs. Main social networks
As a result of survey, we could say that Facebook has a high level of defensive (39%) and conscious
(30%) users. This may mean that Facebook is a mature website in which users begin to notice
security issues about privacy or personal data protection. It is very interesting to see how LinkedIn
has the largest number of uninterested users (78%). We can consider that this is because it is a
professional social network so people use it just for professional motivations and not for social
activities.
Tuenti has the highest level of conscious users (53%). They are happy with the content that Tuenti
offers but are concerned about the security and privacy (e.g. some problems occurred about security
and privacy issues in Spain in the last months). The absence of enthusiastic or uninterested users
means that this website is also mature in the Spanish market.
Twitter has a high level of uninterested users (40%) so we can think that there are some services that
could be improved. The low degree of defensive users (16%) means that they do not find security
problems but a lack of utility: new services required.
42. 42
StudiVZ has the largest number of enthusiastic users (37%). This is good in the sense that users are
happy with the website and they would not change it for other one.
6.5 Cluster Analysis for Motivations
44. 44
6.6 Potential Improvements for social networks
Automatic Classification vs. Opinions
In this cross analysis, we would like to figure out opinions towards social networks for each class. As
it’s seen in the table, we noticed 3 or 4 significant points for each, except from class of sociable
people who shows almost all extreme values for every opinion. According to the class of expressive
people, SNs are useful but at the same time they pointed out that they are most likely exhibitionistic,
dangerous for privacy and time consuming. Thirdly, serious people, who would like to promote a
brand, a company or a group, expressed that SNs are useful and user friendly; as a negative fact they
think that SNs are exhibitionistic. The people who are in the trend followers’ class emphasize that
SNs are useful& user friendly but still they have concerns about privacy. Lastly, curious people
45. 45
pointed out SN are exhibitionistic & dangerous for privacy even if they would like to stay updated
and to get information about others’ lives.
Automatic Classification vs. Most important SN
To cross- check our classifications, we also make analysis concerning most important SNs they use.
The results we got were proving the characteristics of classes. For example, we noticed that curious
people are mostly using SNs such as Facebook, Tuenti, StudiVZ; while serious people tend to use
LinkedIn more which has a professional concept. Moreover, we could say that SNs like Twitter are
used dominantly by expressive people. Concerning about trend followers, it could be seen that they
have membership for almost all popular SNs, even if they do not show interest so much.