Negativism as a news selection predictor

The purpose of this study was to determine whether negativism in a news story is a significant predictor of story selection by journalists. Matched samples of journalists were given 10 news story leads. One sample saw a randomized list of positive and negative leads, while the other sample saw the leads in the same order, but the opposite positive or negative version.

Each subject rated each lead for importance, defined as whether he would select the story for tomorrow's newspaper. A 0-to-100 thermometer scale was used. All subjects also were presented all 10 pairs of positive and negative stories and asked to choose only one version for publication.

The hypotheses were that (1) journalists would rate the negative versions as more important than the positive versions in the split-sample test; (2) journalists would tend to select the negative version over the positive in the paired-version test; and (3) leads having the highest number of news values, as calculated by a news value additivity index, would receive the highest importance ratings from the journalists, and leads with low values, the lowest.

The first hypothesis was only mildly supported. Journalists rated the negative version more important on six of the 10 pairs, but only three showed significant differences. Overall, the difference between the versions was not significant.

The second hypothesis was more strongly supported. Journalists preferred the negative version over the positive in the forced-choice situation nine times out of 10, and four preferences were statistically significant. The overall preference for the negative (63 to 37 percent) also was significant.

The third hypothesis was supported. News value additivity index scores and mean importance ratings correlated positively at +0.79 (p < .001).

Negativism does seem to play a part in the news selection process, though perhaps not as strong as hypothesized. Negative news may hold more information of value than positive and it may influence news selection based on that factor and not raw negativity. Further studies of on-the-job news selections may yield more helpful data.