Analysing the Unequal Effects of Positive and Negative Information on the Behaviour of Users of a Taiwanese On-Line Bulletin Board

<div><p>The impact of social influence causes people to adopt the behaviour of others when interacting with other individuals. The effects of social influence can be direct or indirect. Direct social influence is the result of an individual directly influencing the opinion of another, while indirect social influence is a process taking place when an individual’s opinion and behaviour is affected by the availability of information about others’ actions. Such indirect effect may exhibit a more significant impact in the on-line community because the internet records not only positive but also negative information, for example on-line written text comments. This study focuses on indirect social influence and examines the effect of preceding information on subsequent users’ opinions by fitting statistical models to data collected from an on-line bulletin board. Specifically, the different impacts of information on approval and disapproval comments on subsequent opinions were investigated. Although in an anonymous situation where social influence is assumed to be at minimum, our results demonstrate the tendency of on-line users to adopt both positive and negative information to conform to the neighbouring trend when expressing opinions. Moreover, our results suggest unequal effects of the local approval and disapproval comments in affecting the likelihood of expressing opinions. The impact of neighbouring disapproval densities was stronger than that of neighbouring approval densities on inducing subsequent disapproval relative to approval comments. However, our results suggest no effects of global social influence on subsequent opinion expression.</p></div

An illustration of a posted message with comments.

<p>A schematic representation showing a series of comments attached to a posted message in a PTT board. The comments are recorded in the order they appear.</p

Estimated parameter values of the logistic regression model (without test data).

<p>Note: significance:</p><p>***<i>p</i>-value<0.001</p><p>Estimated parameter values of the logistic regression model (without test data).</p

PTT user’s interface.

<p>A schematic representation showing a typical PTT board on a user’s interface. The posted messages are arranged in chorological order.</p

Estimated parameter values for the randomised data

<p>Note: significance:</p><p>***<i>p</i>-value<0.001.</p><p>Estimated parameter values for the randomised data</p

Scatter plots of phylogenetic profile against different measures of topological importance

<p><b>Copyright information:</b></p><p>Taken from "A network perspective on the topological importance of enzymes and their phylogenetic conservation"</p><p>http://www.biomedcentral.com/1471-2105/8/121</p><p>BMC Bioinformatics 2007;8():121-121.</p><p>Published online 11 Apr 2007</p><p>PMCID:PMC1955749.</p><p></p> (a) phylogenetic profile () against the degree (); (b) averaged phylogenetic profile against averaged degree; (c) phylogenetic profile () against closeness centrality (); (d) averaged phylogenetic profile against averaged closeness centrality; (e) phylogenetic profile () against betweenness centrality (); (f) averaged phylogenetic profile against averaged betweenness centrality. The vertical bars in b, d, f are standard errors

Variance of neighborhood ranks in betweenness and closeness centralities

<p><b>Copyright information:</b></p><p>Taken from "A network perspective on the topological importance of enzymes and their phylogenetic conservation"</p><p>http://www.biomedcentral.com/1471-2105/8/121</p><p>BMC Bioinformatics 2007;8():121-121.</p><p>Published online 11 Apr 2007</p><p>PMCID:PMC1955749.</p><p></p> The figure shows a scatter plot of the variance of neighborhood ranks in betweenness centrality (Var(Rank_B)) against the variance of neighborhood ranks in closeness centrality (Var(Rank_C)). The bold diagonal line represents Var(Rank_B) = Var(Rank_C). Note that most points are below the diagonal. This indicates that a node's neighborhood varies more in betweenness centrality than in closeness centrality