Abstract
The aim of this study is to analyze the reasons behind users’ selection of news results on the news aggregator website, Google News, and the role that news factors play in this selection. We assume that user’s cognitive elaboration of users influences their news selection. In this study, a multi-method approach is used to obtain a complete picture of the users’ news selection reasoning: an open survey, a closed survey, and a content analysis of screen recording data. The results were determined from online news selection of 90 news results from 47 users on Google News. Different news values could be identified as relevant for selection: time-referenced news factors and news factors of social significance were shown to be more important than the news factors of deviance. News cues (presence of a picture, position of a news result, source) were identified as selection reasons regardless of the level of cognitive elaboration during the online browsing process.
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Appendix
Variables of the content analysis of the depicted news results and of the answers in the open survey.
Variables | Content analysis of the depicted news results | Content analysis of the answers in the open survey |
Impact (occurrence of influential persons, groups, or institutions)S | X | X |
Reach (events and developments affecting a large number of people)S | X | X |
Elite locations (places of great political or economic importance)S | X | X |
Facticity (people or institution acting in dynamic or concrete situations)S | X | X |
Success (positive outcome of a dynamic situation and/or action)S | X | X |
Damage (negative outcome of a dynamic situation and/or action)S | X | X |
Controversy (dissent expressed)D | X | X |
prominence (occurrence of a well-known person) | ||
Unexpectedness (unexpected new event or surprising development)D | X | X |
Personalization (focus on single persons while reporting an event)D | X | X |
Emotions (reporting about feelings associated with an event)D | X | X |
Geographical proximity (physical closeness)O | X | X |
Actuality (release date)O | X | X |
Continuity (established topic)O | X | |
Position of the news results on the Google News website (first headline position, mean position or after the scroll line)N | X | X |
Sources of the news results (quality of media offers) N | X | X |
Existence of a picture N | X | X |
Personal relevance | X | |
S news factors of social significance; D news factors of deviance; O not classified news factors in line with Wendelin et al. (2017); N news cues | ||
Inter-coder reliability of users’ perceived content on Google News.
Variables for each news result | Holsti coefficient with order* | Krippendorff’s alpha |
Position | .91 | .91 |
News factor local status | .90 | .69 |
News factor geographical proximity | .78 | .75 |
News factor controversy | .82 | .65 |
News factor reach | .76 | .70 |
News factor impact | .78 | .52 |
News factor prominence | .94 | .88 |
News factor personalization | .90 | .81 |
News factor success | .78 | .30 |
News factor unexpectedness | .88 | .51 |
News factor damage | .69 | .26 |
News factor emotion | .94 | .88 |
News factor recency | .92 | .97 |
News factor facticity News factor picture | .80 1 | .46 1 |
* n = 51 news results | ||
Inter-coder reliability of open-ended reported news values for news result selection.
Name of the variable | Holsti coefficient with order* |
Number of the person | 1 |
Number of the news result | 1 |
Length of the answer | 1 |
Answer given | 1 |
News value visual (picture and position) | 0.98 |
News value impact | 0.86 |
News value prominence | 0.95 |
News value personalization | 0.93 |
News value recency | 0.86 |
News value success | 0.98 |
News value damage | 1 |
News value issue establishment | 0.92 |
News value geographical proximity | 0.91 |
News value elite locations | 0.94 |
News value emotion | 1 |
News value reach | 0.85 |
News value controversity | 0.95 |
News value unexpectedness | 0.98 |
News value personal relevance | 0.92 |
*n = 17 reported reasons for news selection | |
Order of the news factors detected in the content analysis of the selected news results and news values of the open and closed survey.
Content analysis (for each news factor: if it exists or if it exists in the highest characteristic in a selected news result, with the most common one listed first) | Open survey (for each news value: how often it was chosen, most commonly chosen first) | Closed survey (for each news value: assessment of importance, most important first) | |
1 | actuality (max. one hour, n = 67) | actuality (n = 27) | facticity (M = 4.04; SD = 0.95) |
2 | impact (big and biggest, n = 63) | controversy (n = 10) | continuity (M = 3.60; SD = 1.42) |
3 | reach (big and biggest, n = 59) | impact (n = 8) | actuality (M = 3.56; SD = 0.97) |
4 | damage (exist, n = 58) | reach (n = 8) | reach (M = 3.50; SD = 1.40) |
5 | facticity (concrete action, n = 54) | continuity (n = 7) | prominence (M = 3.48; SD = 1.37) |
6 | controversy (big and biggest, n = 49) | geographical proximity (n = 5) | impact (M = 3.33; SD = 1.25) |
7 | personalization (exist, n = 44) | emotion (n = 4) | controversy (M = 3.32; SD = 1.35) |
8 | geographical proximity (big and biggest, n = 40) | prominence (n = 2) | unexpectedness (M = 3.01; SD = 1.14) |
9 | prominence (big and biggest, n = 38) | personalization (n = 2) | damage (M = 2.82; SD = 1.17) |
10 | unexpectedness (exist, n = 14) | success (n = 1) | elite locations (M = 2.71; SD = 1.41) |
11 | elite locations (exist, n = 10) | unexpectedness (n = 0) | emotion (M = 2.32; SD = 1.27) |
12 | success (exist, n = 9) | elite locations (n = 0) | personalization (M = 2.28; SD = 1.24) |
13 | emotion (exist, n = 5) | damage (n = 0) | success (M = 2.26; SD = 1.17) |
14 | facticity (n = 0) | ||
Note.N = 90 selected news results on news aggregator website Google News | |||
© 2019 Walter de Gruyter GmbH, Berlin/Boston
