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Parties, Candidates and Citizens On-Line - Åbo Akademi

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4.4.2. Who is on-line?<br />

Which factors, then, influenced the Finnish c<strong>and</strong>idates’ web presence? A logistic<br />

regression analysis, presented in Table 5, examines three central c<strong>and</strong>idate characteristics:<br />

age, gender, <strong>and</strong> size of the c<strong>and</strong>idate’s party. Put bluntly, is on-line campaigning a<br />

concern for young, male c<strong>and</strong>idates representing major parties?<br />

TABLE 5. A Logistic regression model predicting the c<strong>and</strong>idates’ use of websites.<br />

B S.E. Exp(B) Sig.<br />

Gender<br />

Age<br />

.717 .467 2.048 .125<br />

18–24 1.393 .726 4.028 .055<br />

25–34 1.284 .702 3.611 .067<br />

35–49<br />

Party Size<br />

.077 .492 1.080 .876<br />

Major Party 5.745 .837 312.473 .000<br />

Minor Party 3.567 .502 35.396 .000<br />

Constant<br />

–.2.900<br />

Cox-Snell R 2 = .487; Nagelkerke R 2 = .656; % Correct = 86.8; N = 220.<br />

Note: The dependent variable: 0 = c<strong>and</strong>idate does not have a website, 1 = c<strong>and</strong>idate has a website.<br />

Gender: Male (1); Female (0). Age: reference category (0): 50 years or older. Party size: reference category<br />

(0): Fringe party.<br />

The model presented in Table 5 shows that age 8 <strong>and</strong> party size, in particular, are<br />

significant predictors of having a website. Above all, belonging to a major party is a<br />

crucial factor. 9 Although it is likely that major parties’ c<strong>and</strong>idates may have obtained<br />

assistance from their parties in setting up their individual sites, we do not have empirical,<br />

interview evidence to support such claim. Neither did we note an extensive use of<br />

st<strong>and</strong>ard site skeletons that could have been provided by the parties. <strong>C<strong>and</strong>idates</strong> who used<br />

such templates usually run for minor <strong>and</strong> fringe parties, not major parties. Additionally,<br />

the model reveals an independent age effect; young c<strong>and</strong>idates (the age groups 18–24 <strong>and</strong><br />

25–34) were more likely to go on-line than the older c<strong>and</strong>idates.<br />

8 Since age effects in internet use tend to be generation specific, we used age categories in the model.<br />

9 An additional cross-tabulation showed that 97% of the major party c<strong>and</strong>idates, 79% of the minor party<br />

c<strong>and</strong>idates <strong>and</strong> 12% of the fringe party c<strong>and</strong>idates had own websites.<br />

73

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