Data Collection and Approach
With the recent growing rate of modern social interactions and availability of information, it is relatively easy to come across compelling information on different people about their interests, either public or private. Depending on your knowledge interests and alignment. Some of the information that can be found publicly include:
- Political affiliations of different community members
- Consumer perceptions of different market products
- Media preference, etcetera.
Owing the evolution of media sources, specifically social media. Interaction among different users of a social media platform can be monitored, partially to improve user experience and partially for reasons such as, monitoring criminal activities and by marketers to gain insight on consumer preferences. Additionally, the data can also be used by social scientists to explore relationships among members, treating them as autonomous members of a society drawing conclusions on how they relate to each other and even explore their perception of each other.
Kahne and Bowyer (2018) in their study on the significance of social media on politics note that, “the Internet has become a dominant force when it comes to how campaign funds are raised, information is accessed, perspectives are shared and discussed, and individuals are mobilized to act politically.” In a glance we can therefore argue that, the role of social media in our lives is too monumental to be overlooked and this new digital platform born incubated approximately 20 years ago by the likes of company’s such as Yahoo.
Final Plenary (2012) argue that social media is integral in politics and ought to be used to “involve and inform citizens in public policy-making and in the formation of governments.”
Political polarization often caused by what Michael and McCarty (2012) identify as “centered on the emergence of excessive partisanship and deep ideological divisions among political elites and officeholders.” Abrams and Fiorina (2012) define polarization as “diverging preferences that cluster toward ideological poles.” Research on the preferences of supporters of major political parties indicate that polarization exist among more partisan citizens, (Abramowitz & Saunders, 2008). Malhotra (2014) argue that polarization occurs when different individuals assume political and social groups as separated.
Arguably, in as much as there are a myriad number of causes to polarization among the notable being money and media presence in politics, polarization has got a fair share of its effects on the affected society, this range from:
- Contributing to social mayhem and mistrust among members of a society
- Disruption of social structures through partisan in treating members of a different political ideology
- Transformation of congress institutions making the congress more partisan with centered negotiations among party leaders (Michael and McCarty, 2012)
In this paper, we will explore the alleged polarization in the Australian political scene through exploring relationships among the political leaders of major parties and their friends (supporters). As such, we will identify whether there are partisan political views among the members of a political party i.e. through determining whether a friend of a political leaders is friends to another leader or even more. Additionally, we will examine the relationships among the friends of a political leader and ascertain the existence of the relationships among the friends. The politicians explored for our study are:
- Malcolm Turnbull (Liberal Party of Australia)
- Bill Shorten (Australian Labor Party)
- Michael McCormack (National Party of Australia)
Assumptions and Hypotheses
In undertaking this study we aim to:
- Determine whether there exists polarization in Australian politics, I.e. whether political parties are disjoint
- Utilize data-mining skills to explore social data
- Explore the truth of the fallacy that “Members of different political parties are enemies”
Some of the limitations of our study include the failure to include more political leaders I.e. the independent variables and chose only three as a representation of the Australian political landscape, additionally, we only consider ten friends from each of the three politicians i.e n=30 which statistically is an inadequate sample to represent a population.
To obtain data for our study we imported 10 friends for each of the interest politicians from Tweeter. This would enable us determine existence of a the relationship among the politicians and the friends (supporters). Later on, we imported data of 1000 friends of each of the politician friends, with which we would determine the relationship among the autonomous friends with each other.
To ensure clean data,we checked for outliers and explored the distribution of the data through carrying out descriptive analysis and to determine the nature of our data.
The instruments required for this research project were:
- A tweeter handle and application
- Computer installed with R-studio statistical programming language with required packages
During analysis we made a number of assumptions. This included: that the friends of each politician is also a member of the political party headed by the politician, in addition, all the friends of the friends of a politician are Australian and they are interested in politics. We also assume that there is a relationship between political ideologies and choice of a political party to be a member in, lastly, there is either a joint or disjoint relationship among the variables.
We came up with three assumptions to enable us answer our research questions, these were:
Null hypotheses
Our null hypotheses were:
H0– People are enemies owing to different political ideologies and inclination
H01– Political parties are disjoint
Alternative hypotheses
Our alternative hypotheses were:
H1– People are not enemies despite different political ideologies and inclination
H11– Political parties are not disjoint
This section is divided into five sub-sections of each of the project requirement that has only code and output for our analysis. The analysis is later discussed in the nest section
In this section, we will explore the results of each sub-section as found in the results section.
In examining the relationship among the politicians and their friends, we found out that each political leader had a unique set of friends, I.e. no politician shared friends. Inferring statistically, it may mean that political parties are actually disjoint since their political ideology seem not to be similar enough to instigate bi-partisan support from their loyal friends. Additionally, we conclude that in Australian political matters, loyalty is key among different supporters of a political party. Moreover, this projection of disjointedness validates our use of twitter as a source of data. I.e. it is fairly reflective of a realistic real-world situation.
Results Analysis
From our study, there is evidence of relationships among different twitter users of different friends of the political leaders. From the statistics, about 26 friends are shared by each of the friends (members of a political party). Therefore we do note that, despite political differences, members of a political party still maintains relationships with others of different political inclinations. We can therefore conclude that, political differences does not necessarily indicate hate among different members.
According to Rosenblatt (2013) a social network density “describes the portion of the potential connections in a network that are actual connections.” Therefore, in order to measure a the extent of social relationships, it is imperative to explore the network densities and draw inferences. Rosenblatt (2013) further argues that a lower density imply lack of key connections. For instance the density of our network is 1.639344% indicating sparsity but somehow connected network. Owing the low network density, we may infer that there are no distinct nodes with clearly high social capital
Shah & Lawrence (2017) define homophily as, “the tendency to associate with similar others.” Therefore it maybe only natural for members of different parties to exhibit homophily. From our graph of homophily, we note that there is an element of homophily among the two groups, given a significance level of (alpha=0.05).
Gramoli (2015) on his lecture on nature of graphs says that “A complete graph is weakly balanced precisely when it can be divided into multiple sets of mutual friends, with complete mutual antagonism occurring between each pair of sets.” Therefore from our graph we not that some relationships can be divided into autonomous groups and hence the signed network is weakly balanced. Additionally, there are two negative relationships hence unexpected, i.e the first branch in the hierachical cluster.
Conclusion
From our project analysis, it is evident that:
- Political parties are disjoint I.e. to a large measure their ideologies tend to be different, therefore drawing unique supporters to themselves
- There exists relationships between members of different political inclinations, this may be due to social diversity or acceptance of the element of differences among the members of a society
- Large social networks do exhibit structural balance, i.e. The analysis signed networks are either highly stable or weak.
Our original null hypothesis H0 stated that: “People are enemies owing to different political ideologies and inclination.” We reject the null hypothesis on the grounds that, given existence of relationships among different members of different political groups as evidence from our research results, it indicates that it is not generally true to conclude that political difference automatically translates to hate among the members of the society. Therefore we accept the alternative hypothesis, H1: “People are not enemies despite different political ideologies and inclination.” Our second null hypothesis H01: “Political parties are disjoint.” We reject the second null hypothesis and accept the second alternative hypothesis H11: “Political parties are not disjoint.” Considering the existence of Homophily among the two groups of interest in our research i.e. the labor party and the other two combined, we note that political parties are not entirely disjoint and may have relationships with each other.
Given our research results and analysis we can therefore refute the common fallacy that members of different political parties are enemies and that political parties are outright disjoint. In conclusion, the differences in the society ought to make us unique and give us the chance to celebrate our individual selves as well as respect other people’s choices and not as a source of drawing hate and prejudice as some earlier studies confirm.
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