key: cord-269093-x6taxwkx
authors: Singh, Amandeep; Halgamuge, Malka N.; Moses, Beulah
title: 5 An Analysis of Demographic and Behavior Trends Using Social Media: Facebook, Twitter, and Instagram
date: 2019-12-31
journal: Social Network Analytics
DOI: 10.1016/b978-0-12-815458-8.00005-0
sha: 
doc_id: 269093
cord_uid: x6taxwkx

Abstract Personality and character have major effects on certain behavioral outcomes. As advancements in technology occur, more people these days are using social media such as Facebook, Twitter, and Instagram. Due to the increase in social media's popularity, the types of behaviors are now easier to group and study as this is important to know the behavior of users via social networking in order to analyze similarities of certain behavior types and this can be used to predict what they post as well as what they comment, share, and like on social networking sites. However, very few review studies have undertaken grouping according to similarities and differences to predict the personality and behavior of individuals with the help of social networking sites such as Facebook, Twitter, and Instagram. Therefore, the purpose of this research is to collect data from previous researches and to analyze the methods they have used. This chapter reviewed 30 research studies on the topic of behavioral analysis using the social media from 2015 to 2017. This research is based on the method of previous publications and analyzed the results, limitations, and number of users to draw conclusions. Our results indicated that the percentage of completed research on the Facebook, Twitter, and Instagram show that 50% of the studies were done on Twitter, 27% on Facebook, and 23% on Instagram. Twitter seems to be more popular and recent than the other two spheres as there are more studies on it. Further, we extracted the studies based on the year and graphs in 2015 which indicated that more research has been done on Facebook to analyze the behavior of users and the trends are decreasing in the following year. However, more studies have been done on Twitter in 2016 than any other social media. The results also show the classifications based on different methods to analyze individual behavior. However, most of the studies have been done on Twitter, as it is more popular and newer than Facebook and Instagram particularly from 2015 to 2017, and more research needs to be done on other social media spheres in order to analyze the trending behaviors of users. This study should be useful to obtain knowledge about the methods used to analyze user behavior with description, limitations, and results. Although some researchers collect demographic information on users’ gender on Facebook, others on Twitter do not. This lack of demographic data, which is typically available in more traditional sources such as surveys, has created a new focus on developing methods to work out these traits as a means of expanding Big Data research.

criteria, and data analysis [8] . The next section is the result section which provides the statistical analysis and the percentage of research completed on different social media. The result section includes a table which provides the research paper analysis according to the year along with pie chart figures, data collection, and behavior analysis methods and classifications based on different methods with line graphs [9] . The next section is a discussion on the given topic and the last section is the conclusion of this research work.

Data were collected from different conference papers published in the IEEE. From these papers, different methods of analyzing the user behavior [10] was assessed. This report is based on a review of the published articles and analyzes the methods they have used. The data are given in a tabular form.

Data were collected from 30 various journal papers from the IEEE library regarding the analysis of the user behavior using social media from 2015 to 2017. The collected data were related to Facebook, Twitter, and Instagram in different countries [11] . The attributes that were used for data collection were: applications, methods used, description of the method, number of users, limitations, and results. This raw data is presented in Table 1 [32].

The different data attributes used to analyze the papers are given in Table 1 . This included the following: author name, applications, methods used, detail of methods, number of users, limitations, and results. Data were gathered relating to different social networking sites [17] . In our analysis, the different methods that have been used by researchers to analyze the user's behavior are explored. In this research, three different social media datasets have been collected, which represents the methods and technologies used to understand the behavior of the users.

The raw data presented in Table 1 specifies the attributes that were used to conduct this research. We pooled and analyzed 30 studies based on the impact of variables used in their studies. The descriptive details of the study based on the publication year were then analyzed to observe the behavior of the social media user from 2015 to 2017. A comparison of the methods they used to investigate the behavior of users was then done.

This research included papers from the last 3 years from 2015 to 2017. All papers used data from Facebook, Instagram, and Twitter. Privacy is major concern Algorithm for news feed is not known Filtering is not done properly [16] It has been observed that individuals who are friends with each others have similar interests Two evaluation metrics were used to judge the performance of classifier ROC and PR used to 

The aim of this research is to know the methods used by researchers to predict the behavior of social media users. In this research, data were collected based on the use of three different social networking sites such as Facebook, Instagram, and Twitter. A random user list was used to analyze the behavior. In our final analysis, we pooled the data, which showed a statistically significant difference in various parameters (published year, methods, results, and limitations) for different social media sites. The results section includes the percentage of research on the three social networking sites, research papers according to year with bar graph representations, data collection and behavior analysis methods and classification based on the different methods with line graph representations.

We performed statistical analysis to organize the data and predict the trends based on the analysis. This showed the different social media sites used based on the data given in Table 1 .

As shown in Fig. 1 and Table 2 , 27% of data was based on Facebook users, 23% of data was based on Instagram users, and 50% of data was based on Twitter users. As such, it is clear that Twitter is used more than other two social media sites for the analysis of the behavior of users. Table 3 

Data collection techniques and behavior analysis methods used by different studies are shown in Table 4 .

The behavior of users can be analyzed using different methods as shown in Table 5 . Fig. 3 is based on the classification of papers based on the different methods used and it is clear that the researchers have used analysis techniques more than others and they have rarely used coding rules.

In this analysis, we observed that the amount of studies on Facebook and Instagram in the period from 2015 to 2017 was low, so there is a need of more research in these important areas.

This review study will help the readers to understand the different methods that the authors have used in their research studies on behavior analysis in social media. An examination of the different methods of behavior analysis carried out with the help of social media is the main aim of this research. Thirty research studies were collected and analyzed to understand the personality of individuals who use social media such as Facebook, Twitter, and Instagram. Only three types of social network sites were included in this research. This analysis from the reported studies gives an overview of methods used to predict the personality of social media users.

As seen from Fig. 1 , 50% of research was done on Twitter from 2015 to 2017, whereas as the other two social networking sites, Facebook and Instagram, only had 27% and 23%, respectively. Moreover, some studies [14, 21] proposed more than one method to analyze individuals' behavior. A major issue in this area is the security and privacy of the information that the users put on the social media. However, some of the studies included in this review provided suggestions and methods to help secure the personal information of users. Many authors also discussed machine learning technique to observe the personality of social networking site users.

The results showed that most of the research completed in 2016 were on Twitter rather than Facebook and Instagram. In 2015, most research was done on Facebook and the least research was done on Instagram. On the other hand, in 2016 Twitter has the highest numbers of research papers and Facebook had the lowest numbers. In 2017, Twitter and Instagram had the highest number of research paper while Facebook had none at all. Data collection and behavior analysis methods provided by authors were collected as raw data and analyzed. A classification based on the methods used by the authors for analysis was created.

Previous review studies did not include the limitations and number of users' attribute in their analysis. We have included these two attributes in Table 1 to make the research more specific and easy to understand for the readers [13] .

The analysis of the papers indicated that Twitter has been the most used to predict the personality of social media users. Considering Table 1 , there is a need for more variety in research methods on Instagram to understand the behavior of users.

A cut-based classification method was used to analyze the behavior of Twitter users by Bhagat et al. [4] . From the analysis done by these authors, they have concluded that cut-based classification method can be extended in the future to provide GUI for users for polarity classifications and subjectivity classifications. Real-time user messaging can also be analyzed in the future [18] .

This review study is based on the analysis of behavior of individuals, who use social network in their daily life. This study benefits readers as it helps to identify the methods used by different researchers and the number of researchers that applied these methods. This review study provides a clear description of the methods, limitations, and results that have been used by previous researches in studies during 2015-17.

More than 37% people of the world use social media; however, the way social media users interact with each other vary greatly. There are demographic and behavioral trends from the Facebook, Twitter, and Instagram that are discussed in Table 6 .

In this review paper, we have reviewed and analyzed data collected from 30 different published articles from 2015 to 2017 on the topic of behavior analysis using social media. It is found that there were 69 different methods used by the researchers to analyze their Table 6 Demographic and Behaviour Trends From the Different Social Media According to age: Age group between 45 and 55 use more Facebook than Twitter and Instagram. More than 79% of this age group use Facebook according to current trend Use of smart phones: Another reason of using social media have been increased in the past year is smart phones. Smart phones have more visual interaction and people can access the social media easily. Advancement in the mobile phones play very important role in the increased users of social media According to location: More people use the social media while they go out for dinner with family and friends. Other locations where people like to use social media is gym, cinema and home specially in lounge room area more than other rooms According to time: More than 70% people use internet in the evening and 57% people use as a first thing in the morning. There is minimum use of social media during Breakfast, lunch, at work and commuting Frequency of using social networking sites: More than 35% people use social media more than five times a day as compared to 20% people who never use social networking site in a day. There are only 3% people who use once a week APPS: More than 68% use apps to access the social media and fewer people use websites to access the social media data. From these methods, the most common technique to analyze the behavior of individuals was analysis techniques. From this study, it is clear that there is need for more research to predict the personality and behavior of individuals on the Instagram. This study found that 50% of research was done on Twitter and 11 different analysis techniques were sued. While reviewing the research articles, it was clear that the researchers have used more than one method for data collection and behavior analysis. Table 1 has all the data analysis of the paper reviewed in the study. Furthermore, unlike past research papers, this chapter included the attributes of the number of users and the limitations of the work done. These studies mostly focused on Twitter with some research on Facebook and Instagram. In this research paper, we have attempted to fill the gap by including the number of users and limitation attributes. There are some challenges to find the solutions to the issues that have been discussed, but these require urgent attention. This study should be useful as a reference for researchers interested in the analysis of the behavior of social media users.

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