Behavioural patterns and inclinations

Some well observed and well-documented behavioural patterns occur in online political discussion and were anticipated to feature either overtly or implicitly in fieldwork.

Homophily

‘…people’s personal networks are homogeneous with regard to many sociodemographic, behavioural, and intrapersonal characteristics. Homophily limits people’s social worlds in a way that has powerful implications for the information they receive, the attitudes they form, and the interactions they experience.’ (McPherson et al. 2001)

It is understood that people tend anyway to mix with others like themselves, a well-documented phenomenon which might underlie much observed online behaviour, and through which there are occasional contradictions of expressed belief and action. Homophily can now be quantified much more easily thanks to digital storage of data. People are similar to those nearby in a social networks for two reasons, one they come to be like their friends through to social influence and two they tend to make links with similar others in a process called ‘selection’ (Crandall et al. 2008). Indeed, and unsurprisingly, many online communities are built around groups of people who are similar socially.

48 | P a g e A study on Twitter, where people are potentially exposed to a wide range of views showed

exchanges amongst like-minded individuals can strengthen group identity, whereas those between different-minded people reinforce in- out-group affiliation. Further, results show that while people are exposed to broader viewpoints than they were before, they are limited in their capacity to engage in meaningful exchange (Yardi & Boyd 2010). A US study of Democrat and Republican supporters indicated higher levels of homophily amongst Democrats except where Republicans were following official Republican accounts (Colleoni et al. 2014). Homophily is so strong a predictor that entire communities on Facebook can be modelled by extrapolating from a fifth of a population (Mislove et al. 2010). Researchers looking at data from a music channel could predict real friendships by comparing interaction, shared interests and location online (Bischoff 2012). There is a high level of similarity among users close to each other in a social network suggesting that users with similar interests are more likely to be friends, so metadata should predict social links. Social networks constructed from topical similarity do capture real friendship accurately (Aiello et al. 2012). Different types of homophily apply to different types of users on Twitter, for example, users with similar number of followers and followed tend to live and work near each other, and show similar views (De Choudhury 2011). Nonetheless, studies show that superficial or negative exposure to out-group members can worsen division and increase hostility. Just putting different groups in the same place is insufficient and can aggravate tribalism (Chua 2018).

Homophily exerts significant effects on social media meaning participants often hear similar views and mix with like-minded others, so this phenomenon relates to the conceptualisation of ‘echo chambers’ discussed further on.

49 | P a g e Polarisation

Political polarisation is not unique to social media and there are mixed views about any causal relationships. Affordances such as closed groups and an on-tap supply of confirmation bias have been speculated to support polarisation, although this is contested. There is not a universal consensus and indeed one study suggested the opposite effect, most social media users are in ideologically diverse networks, and exposure to this has a positive effect on moderation, potentially reducing mass polarisation (Barberá 2015).

Another study concluded that social media and the internet are not the cause of political

fragmentation as people use them to broaden their horizons and consume media widely, and echo chambers may not be such a threat as only a small proportion of the population is influenced by them (Dubois & Blank 2018). A South Korean study using panel data from 2012 to 2016 shows that social media does not directly force polarisation, but encourages participation and engagement per se, which itself tends to direct users towards ideological poles, so an indirect effect (Lee et al. 2018).

Group polarisation, the idea from social psychology that refers to the tendencies within groups to develop more extreme ideas than members’ prior preferences suggests that a group's attitude toward a situation can become strengthened and intensified after group discussion, so-called attitude polarisation (Myers & Lamm 1975). This can often be observed in political party focused discussion and is evident in the debates around Scottish independence, ‘Brexit’ and the party leadership of Labour’s Jeremy Corbyn. It is in line with May’s Law of Curvilinear Disparity which suggests that members of political parties tend to be more ideological than both the party leadership and its ordinary voters (May 1973).

50 | P a g e From the perspective of social comparison theory, group polarisation happens owing to an individual wish to be accepted and be seen favourably by their group, so also in line with Goffmann, whose theories of the presentation of self are discussed further in the methodology chapter. This theory suggests people first compare ideas with others in the group and assess their values and

preferences. Then to be accepted, they might take a position that is like that of the others but a bit more extreme. This allows the participant to support the group's beliefs while showing leadership.

Normative influencing is more likely to be present when discussing contentious topics, where group harmony is considered important, where there is a person-centred ethos in the group and for responses made in public (Isenberg 1986). Linked to polarisation, scholars have identified backfire effects that lead to people reinforcing their earlier positions because of motivated reasoning, different interpretation of identical facts or other reasons (Tucker et al. 2018)

In The Righteous Mind: Why Good People are Divided by Politics and Religion social psychologist Jonathan Haidt wrestles with the possibility of reaching common ground between political poles.

Well ahead of more widespread observation in the wake of the election of Donald Trump as US President, Haidt argued that people are too quick to dismiss the view of others politically, but to the question many people ask about politics — ‘why doesn’t the other side listen to reason?’ - he suggests we are simply not designed to do so. In fact, he argues, neurological research shows that people reach conclusions first and then rationalise them afterwards. People do reason but do so mainly in order to support their own conclusions. So, they will repeatedly marshal arguments to justify a point of view. Haidt maintains that we do this because we compete for social status, and the ability to influence others is central to this. He suggests that if you want to change people’s minds, you should not appeal to their reason but the underlying moral standpoints being defended (Haidt 2012).

51 | P a g e In Moral Tribes Joshua Greene draws on his own ‘dual-process’ theory, neuroscience and

evolutionary psychology to discuss how our intuitions about ethics are enacted in practice. Greene’s dual processing research using MRI scanning showed that people making judgements over personal moral dilemmas use regions of the brain linked to emotion that were not usually activated by less personal choices. They found that for the dilemmas involving ‘personal’ moral questions, people making an intuitively unappealing choice did so after longer reaction times than those who made less emotionally challenging decisions. He suggests we have a natural inclination to cooperate and predisposed to do what we see as best for a group if pressured by time, to go with gut instinct.

However, co-operation can be overridden by rational reflection. Regarding inter-group harmony he suggests that these automatic responses hit a snag. The same loyalty that supports co-operation within communities leads to hostility between them. He incidentally proposes a ‘metamorality’ upon which we all can agree. He proposes utilitarianism, or ‘deep pragmatism’ as the way forward for politics (Greene 2014).

What might make people change their minds? Bayesian theories of information processing suggest that people would modify their political positions faced with new information, in line with what they have learned (Tucker et al. 2018). Responses from this field research indicate that participants themselves often resist changing but do acknowledge change over time. This might be triggered by an unexpected insight into an opposing view or candidate, or they may reach a ‘tipping point’.

Johnston, Lavine, & Woodson considered the factors which might make people switch from a partisan position where they side reflexively, to a more considered one, looking at additional information. They note that earlier work indicates that variation in political reasoning is triggered by anxiety, but they ask whether an overall pattern of emotions confirms or disrupt partisan

expectations. They look at anxiety, anger, and enthusiasm as influential factors and suggest that

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‘expectancy-violating emotion’ increases deliberative reasoning and suppresses partisan reactions, and vice versa (Johnston et al. 2015).

Echo chambers and filter bubbles

‘…media’s greatest potential lies in its impersonal exposure of audiences to cross-cutting views, an essential form of communication in a highly pluralistic society.

In order to sustain this benefit, however, news media must be structured so as to limit the public’s capacity for selective exposure (Mutz & Martin 2001).

The idea of the social media political echo chamber is now well-established and has generated much media and academic discussion. The phenomenon is variously characterised as the product of invisible algorithms (filter bubbles), innate prejudice or media divisiveness. The UK’s Guardian newspaper even sought to address the problem with a ‘break out of your bubble’ feature

summarising key conservative news links. Studying how Italian and US Facebook users related to two different narratives researchers showed participants’ tendency to promote their preferred versions and thence form polarised groups. They suggest confirmation bias helps explain decisions about whether to spread content, creating informational cascades within communities. Aggregation of preferred information reinforces selective exposure and group polarisation. Users tend to note only confirming information and to ignore rebuttals (Quattrociocchi et al. 2016). Group conflict during political turmoil may encourage selective avoidance and social-informational communities becoming more insular (Zhu et al. 2017). People mostly share content to support their political views. Political posts have more shares than reactions. Evidence suggests the more partisan the content, the more that tribe will share. So, the more someone likes affirming content the less divergent viewpoints they will see (Rayson 2017).

Garimella et al identify the two components in the phenomenon of echo chambers - the opinion that is shared (‘echo’) and the place that allows its exposure (‘chamber’ or the social network) and

53 | P a g e examine how these interact. They concluded that Twitter users are, to a large degree, exposed to political opinions that agree with their own and that users who try to breach echo chambers by sharing diverse content suffer in terms of their network centrality and content appreciation. They also study the role of ‘gatekeepers,’ that is, users who consume diverse content but produce partisan content in the formation of echo chambers. They conclude that partisans are quite easy to identify, but gatekeepers prove to be more challenging (Melo & Paulheim 2017).

Investigating two million retweets collected during 10 days in connection to the EU Referendum and the 2017 UK general election, a study showed that people tend to connect to each other in

heterogeneous networks when it comes to online news consumption and that there is a positive relationship between the news exposure of a user and that of their friends. However, the breadth of news exposure within a personal network is in general wide enough to incorporate many different sources. People are more likely to pass on information from ideologically similar contacts and data shows that Labour supporters are rarely engaging with Tory supporters via retweets and vice versa (Johansson 2018).

UK Political groups are reflected in online communities of varying cohesiveness and ‘echo chamber’

can describe how they engage. Those similar affiliations tend to share news from sites ideologically similar to their affiliation, the extent of this varies by party. People with more polarised views tend to be more inward-facing than the more moderate. Groups are more likely to interact with others who are ideologically aligned. Discussions of issues show that certain topics are much more discussed by some political groups than by others and these topics relate to those parties’ main political interests (Krasodomski-Jones 2016).

54 | P a g e Pariser argues against the neutrality of the internet, noting that search engines make suggestions determined by page rank algorithms and (at that point) by using 57 different indicators relating to previous search topics, past pages visited and the user’s location. When people post, friends who have similar political views show up more in newsfeeds than those with opposing beliefs, and he experienced not seeing posts by conservative friends. Yet at the same time he also challenges the notion of context collapse and having one integrated identity and argues there are differences between the work self’ and ‘play self’ and other selves in different online places, and a difference between ‘you are what you click’ and ‘you are what you share’. Also, while one might believe it is possible to know a personality based on evidence found online, even this would be selective, and prone to confirmation bias, he suggests (Pariser 2011).

Facebook’s data science team indeed tested the “filter bubble” theory and published the results. The study suggests that using Facebook means readers tend to see significantly more news popular among people who share their beliefs, so there is significant ‘filter bubble’ effect, but smaller than might be expected (Bakshy et al. 2015). They calculated that a reader is about 6 per cent less likely to see content from opposing political views. Friend choice, in other words, matters more than the algorithm.

Normative peer pressures

The urge towards conformity and its effects on choice-forming and decision-making is important to understanding group influence in political behaviour. It is interesting to explore how this might work in a mediated public space like social media. ‘Normative social influence’ has been defined as ‘the influence of other people that leads us to conform in order to be liked and accepted by them’ and an urge to fulfil others' expectations through acceptance of evidence about reality provided by others (Aronson et al. 2010). It stems from the fact that people are social beings. Motivations include the

55 | P a g e urge to build and maintain relationships, and to manage self-concept (Cialdini & Trost 1998). Peer pressure can however lead to people complying in public but not necessarily privately accepting a group's social norms (Forsyth 2011). This is linked to an idea from social psychology, ‘pluralistic ignorance’ where most members of a group privately disagree with a norm, but mistakenly believe that most of the others accept it, and therefore go along with it. Effectively, it is bias about a social group held by its own members (Krech & Crutchfield 2011). This can perhaps be seen in the ‘shy Tory’ phenomenon, those who vote Conservative but feel ashamed to admit so in public.

Informational social influence or ‘social proof’, is a phenomenon where people mirror the behaviour of others to reflect the accepted style for a situation (Aronson et al. 2010). The effects can be observed in the tendency of large groups to conform to certain beliefs or behaviours irrespective of whether they can be deemed objectively right or wrong – sometimes called ‘herd behaviour’. A so-called ‘information cascade’ happens when an individual observes the actions of others, makes inferences and then – despite possible contradictory information, engages in the same behaviour (Easley & Kleinberg 2010). Social proof is also observable on social media platforms. The number of

‘followers’, ‘views’, ‘likes’, comments etcetera a user has affects positively how others see them. A user with multiple millions of followers is seen as having a better reputation than a similar profile with significantly fewer, resulting in further, faster growth and greater engagement. Success breeds success, and in fact a vast industry of ‘ghost followers’ exists to increase social proof on social media.

This ‘rich get richer’ idea can be backed up by network modelling (Aparicio et al. 2015).

Studies have shown the power of group influence on persuasion and a low level of awareness of this.

One study series looked at the under-acknowledged role of social identity. Even when making a real effort, attitudes toward a policy proposal seemed to depend almost completely on the formal position of a person’s party-political allegiance. This overrode both the objective content of a policy

56 | P a g e and a participants' ideological beliefs and was seemingly led by a shift in the perceived detail of the policy and its moral connotations. Still, participants denied having been influenced by their political party, although they believed that other individuals, especially their ideological adversaries, would be (Cohen 2003). As will be seen in field research results, self-awareness does not always come easily.

Partyism

‘Partyism’ is increasing (Sunstein 2015). Party identification is often an enduring emotional attachment and party identities are a reliable indicator of attitudes and behaviour. Partisans will support their party even in the face of changing personalities and policies. Amongst the complexity of political issues, party lines help direct towards positions to support (Dalton 2016). Hostile feelings for opposing parties are ingrained in many voters' minds, and party-based affective polarisation is as strong as polarisation based on race. Party cues also affect non-political judgments and behaviour.

The willingness of side-takers to be openly hostile towards opposing partisans relates to a lack of norms around expressing negative sentiments. Increasing partisan behaviour is a potential incentive for those in power to act confrontationally rather than cooperate. (Iyengar & Westwood 2015).

People have stronger attachments to political parties than to the groups those parties represent.

Partisans discriminate against opponents in a way that exceeds discrimination based on religion, language, ethnicity or location, even when these are based on intense longstanding conflict.

Animosity is affected by ideological proximity, partisans most distrust those furthest from them ideologically and effects of partisanship on trust erode when party and social ties collide (Westwood et al. 2018). This is an interesting idea to consider in relation to in-party conflict.

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