*5.2. Virality*

Now, focus turns to the impact of article virality. Data related to this topic is presented in Figures A28–A30.

Figure A28 shows the impact of the virality of an article on its perceived trustworthiness. There are no clear correlations between focus on virality in trustworthiness assessment and age. There is a notable negative correlation between focus on this factor and educational attainment, with 50% of some high school respondents indicating a "great deal" or "a lot" of focus on this and under 30% of doctorate holder indicating similar focus. There is also significantly more interest among females in article virality as an assessment criteria.

Figure A29 indicates the level of focus that Americans think others place on article virality in assessing credibility. Two peaks (at 25–29 and 60–64) are visible with a depression between them. The educational attainment data shows a positive correlation between educational attainment and focus on virality on the lower-education end of the spectrum. A second positive correlation is shown in the range between associates, bachelors and master's degree holders, when considering the combined "great deal" and "a lot" data. Females believe others have moderately more interest in article virality than males, with only about two-thirds of the level of "none" responses of male respondents.

Finally, Figure A30 shows the Americans' believed-ideal level of virality impact on article credibility assessment. Like with the self-perception data, the ideal-perception data for age groups has no clear patterns. The educational attainment data shows a negative correlation between higher education level and interest in using article virality for assessment purposes. This mirrors the self-perception data and is significantly different than the others-perception data. Like with the self- and other-perception data, females evidence greater interest in article virality in assessing its credibility. Notably, 30% of males indicate that virality should have no impact on this assessment, which is higher than the self-perception and others-perception data, showing that some males feel that they and others are giving an undesirable level of focus to this criteria.

## *5.3. Controversy Level*

Next, focus turns to the impact of the controversy level of the article on its perceived trustworthiness. Data related to this is presented in Figures A31–A33.

No clear association is visible between the article trustworthiness and age, beyond the 35–39 age group. Between the 18-24 and 35-39 age groups, the level of "great deal" responses consistently declines with age; however, the number of "a lot" responses nearly perfectly compensates for this drop, making the combined "great deal" and "a lot" response levels similar through these age groups. There is minimal variation between the impact of controversy level on article trustworthiness across education levels. Males and females have very close response levels; however, slightly more interest about controversy level in article assessment is shown by females in Figure A31c.

Figure A32 shows the perceptions of Americans about the importance that others place on an article's level of controversy in assessing its trustworthiness. A small decline in controversy level importance is shown, for the "great deal" and "a lot" levels between 24–29 and 55–59 age groups. Notably, the 60–64 and 65 and older groups are both higher than the 55–59 group and the 18–24 group has one of the lowest levels of focus on article controversy level.

Among the lower educational attainment levels there is an association between greater education and greater focus on article controversy level in determining trustworthiness. Comparing male and female responses, in Figure A32c, no notable gender differences are apparent.

Finally, Figure A33 shows the perceived ideal level of focus on article controversy as part of article trustworthiness assessment. In the age level data, there are (again) minimal patterns. A positive correlation between age and increased ideal focus is shown between the 18–24 and 30–34 age groups and, separately, between the 35–39 and 45–49 age groups. The data related to educational attainment also does not paint a clear picture, with a slight upward trend amongs<sup>t</sup> the some high school and associates degree educational levels, at the "great deal" and combined "great deal" and "a lot" levels. However, this is also a downward trend, at the "moderate" level between these same educational levels. The data also shows more ideal interest in controversy level amongs<sup>t</sup> female respondents.

## *5.4. Reading Level*

Finally, focus turns to the impact of the article's reading level on respondents' perception of article trust. This data is presented in Figures A34–A36.

Figure A34a shows significant variability by age level and no clear trends. Figure A34b shows two positive correlating trends between greater education and greater focus on reading level. No significant difference exists between male and females, with regards to responses to this question, as shown by Figure A34c.

Figure A35 shows Americans' perceptions of others' focus on article reading level in assessing article trustworthiness. Again, with the age group data, significant variation and no clear trends are present. There are also no notable trends in the education level data other than a decline shown in the combined "great deal", "a lot" and "moderate" level between bachelor's, master's and doctoral degree holders. Once again, no notable difference exists between male and female responses for this question.

Finally, Figure A36 shows the perceived ideal levels of focus on article reading level as part of trustworthiness assessment. The age data, again, shows no clear trends. The educational level data shows a positive association between additional education and focus between the some high school and some college levels. This is present at the combined "great deal" and "a lot" as well as the combined "great deal", "a lot" and "moderate" levels. Finally, there is again no notable difference between gender responses for this question, as was the case with Figures A33c and A34c.

#### **6. Implications of Analysis**

The data presented in Sections 4 and 5 contains numerous trends that illustrate how individuals from different demographic backgrounds make their news content consumption decisions. These trends may inform the construction of effective labeling mechanisms for news content. All three variables of analysis (age, education and gender) were shown to have multiple correlations with added or reduced emphasis for different article characteristics. For the data presented in Section 4 (and which is summarized in Table 4), twelve characteristics show differences in perceived importance based on respondents' age, twenty-three show differences in based on respondents' education level and fifteen show differences based on respondents' gender.

While the implications of all of these comparisons are potentially important to determining how to best serve their respective demographic groups, a few serve as notable examples. The data showed, as illustrated in Figure 2, that males place more weight on the publisher than do females. Conversely, as shown in Figure 3, females were shown to place more weight on the date of publication than did males. These differences would potentially inform what details would be most relevant to different users (if their own personal preferences were not known) and may inform what information is presented, as well as the order that it is presented in. Similarly, the importance of the publication date was shown (in the data presented in Figure 4) to decline with respondents' age, while the importance of an author's and publisher's political alignment were shown to increase with education level (see Figures 5 and 6). It is also notable that both the self (Figure 6) and

ideal (shown in Figure 7) levels for author's political alignment show the same pattern, indicating that respondents' aspirations and actual actions are aligned. This pattern is present for several article characteristics.

**Table 4.** Summary of trends and differences by age, education and gender for article title, publication date, publisher, author, sponsor and political alignments.


**Figure 2.** Showing that males place more weight (at combined "great deal" and "a lot" levels) on the publisher than do females.

**Figure 3.** Showing that females place more weight (particularly at the combined "great deal" and "a lot" levels) on publication date than do males.

**Figure 4.** Showing that the ideal level of focus on publication date declines with age.

**Figure 5.** Showing that the weight placed on author's political alignment increases with education level.

**Figure 6.** Showing that the weight placed on publisher's political alignment increases with education level.

**Figure 7.** Showing that the ideal weight that is placed on author's political alignment increases with education level.

It is also notable that the trends present are not all the same. For example, factors that increase and decrease with age and education were both identified. Some factors were shown to be similar between males and females, while others were shown to be given additional weight by males or females. Given this, it is critical to incorporate demographic-specific article information when labeling online content for combatting fake

news. Furthermore, it is also key to understand that the information that will be best to present may not be a combination of key information identified for each demographic group considered. Rather, it would be prudent to provide the most relevant subset of information to each individual, which can be partially determined by their demographic group memberships.

Table 5 presents similar data as Table 4 for the four article characteristics (quantity of opinion statements, virality, controversy level and reading level). Again, age, education and gender-correlated levels of focus were present. Four characteristics showed an interest level correlation with age. Eight showed an interest level correlation with education and seven showed an interest level correlation with gender. Even within this smaller number of factors, those with both positive and negative correlations were demonstrated. This further emphasizes the potential benefits of providing demographically-targeted information to combat the spread of fake news. This data also facilitates, the comparison of respondents' perceptions of their and others' actions and their aspirations. Figures 8 and 9 illustrate, for example, how females evidence higher interest in article virality and also consider this metric to be ideally focused on, to a greater extent than males.

**Table 5.** Summary of trends and differences by age, education and gender for article quantity of opinion statements, virality and controversy and reading levels.


The differences between individuals' self-perception of focus, perception of others' focus and perception of the ideal level of focus on article characteristics and attributes were also considered and are presented in Tables 6 and 7. Once again, considerable demographic differences were shown. For the article attribute data (summarized in Table 6), twenty-two of the comparisons (between self and others, self and ideal and others and ideal) had an agecorrelated trend. Thirteen had an education level correlated difference and twenty-two had a gender-correlated difference. The attribute data, shown in Table 7, had ten age-correlated differences, seven education level correlated ones and 11 gender-correlated differences.

**Figure 8.** Showing greater interest article virality by females (self-perception).

**Figure 9.** Showing greater ideal interest in article virality by females.

**Age Education Gender** Title Self-Others Others give more weight to title Others place more focus than they do, at most levels 25% of both genders say others place more weight on than them Self-Ideal At many levels, more indicated self-belief than importance No clear pattern No notable difference Others-Ideal Others less across ages Others less at all levels except Ph.D. (same) Others less for both genders, females have slightly higher comparative others importance at "great deal" level Publisher Self-Others Similar Similar Similar; less females reporting "great deal" Self-Ideal More focus placed on publisher than ideal in 7 of 10 age groups No clear trend Similar; males have greater focus at "a lot" level Others-Ideal Others place more focus on publisher than ideal in 7 of 10 age groups Others place more focus than ideal in 5 of 7 categories Males perceive others having more focus than ideal; females perceive others having similar to ideal focus level Publication Date Self-Others No clear pattern Mostly similar Greater importance to others reported among both genders; females similarly place greater importance Self-Ideal More ideal focus than reported self-focus at most levels No clear pattern More ideal focus than self-focus for both genders at "great deal", "a lot" and "moderate" levels Others-Ideal More ideal focus than reported others focus at all but one level More ideal focus than reported others focus at all but one level More ideal focus than reported others focus at "great deal", "a lot" and "moderate" levels Author Self-Others Seven of ten have higher self than others at combined "great deal" and "a lot" levels All but Ph.D. level report higher for self than others Similar for males; lower level of females reporting importance for others at combined "great deal" and "a lot" levels Self-Ideal Six of ten report higher self than ideal focus level No clear trend Lower ideal than self for both genders Others-Ideal Six of ten report lower others than ideal focus No clear trend No clear trend for males; females report others less than ideal at "great deal" and "a lot" levels Article Sponsors Self-Others Younger age groups report less focus than others; older age groups report more No clear trend Males have notably more "great deal" respondents for self than others; females have marginally more. Self-Ideal Nine out of 10 report more focus than ideal No clear trend Males and females report more focus than ideal at "great deal" and "a lot" levels Others-Ideal Seven of 10 age groups report others have more focus than ideal All but one education level, respondents report others have more than ideal focus Both males and females say others have less "great deal" interest than ideal and more "a lot" interest than ideal Author's Political Alignment Self-Others Eight of 10 ages indicate greater others focus than self-focus Five of 7 education levels report greater others focus than self-focus Both males and females report greater others' focus than self-focus Self-Ideal Nine of 10 ages report more self-focus than ideal focus. Six of 7 report more self-focus than ideal focus Males and females report more self-focus than ideal focus; more significant difference for males Others-Ideal More others' focus than ideal at all age levels Six of 7 education levels report more others' focus than ideal focus Males and females report more others' focus than ideal focus; more significant difference for males

**Table 6.** Comparison of self-perception to perception of others, self-perception to ideal-perception and perception of others to ideal-perception for the impact of article title, publisher, author, publication date, sponsors and political alignments.


**Table 6.** *Cont*.

**Table 7.** Comparison of self-perception to perception of others, self-perception to ideal-perception and perception of others to ideal-perception for the impact of article quantity of opinion statements, virality and controversy and reading levels.


Two examples are illustrative. Figures 10 and 11 show how respondents have a lower aspiration to consider authors than actually do. This indicates that Americans, collectively, believe that they don't give enough weight to article authors. Conversely, more respondents indicated focus (as shown in Figures 12 and 13) to an article's publisher's

political alignment, indicating that Americans believe that they give—collectively—too much focus to this article attribute.

**Figure 10.** Showing the level of focus given by respondents to articles' authors.

**Figure 11.** Showing the level of focus that should, ideally, be given to articles' authors.

**Figure 12.** Showing the level of focus given by respondents to articles' publishers' political alignment.

**Figure 13.** Showing the level of focus that should, ideally, be given to articles' publishers' political alignment.

These comparisons are of particular interest as respondents' perspective regarding what is ideal and their comparative practices may indicate areas where they have motivation to change. Similarly, perceived differences between respondents own perceptions and their perceptions of others' beliefs is informative both as to how others may react to data as well as to understanding where respondents see themselves relative to others in their social circles. Comparing respondents' perceptions of others' focuses on different characteristics and what they perceive as an ideal level of focus can be similarly insightful.

#### **7. Conclusions and Future Work**

This paper has discussed the difficulties and dangers presented by deceptive online content which is commonly known as "fake news". To attempt to understand why deceptive content spreads and what can be done to prevent its spread, without requiring a solution such as governmen<sup>t</sup> censorship of content, it has analyzed the different factors that individuals consider when making news consumption decisions. Specifically, it has considered the impact of different online article characteristics and qualities on trustworthiness perception. Questions have targeted three different perceptual filters: perception

of self, perception of others, and perception of the ideal. This allows for comparison of perceptions of "what is" and "what ought to be."

As different individuals may give different levels of weight to different characteristics and qualities, this paper has evaluated the impact of the different characteristics and qualities in terms of the key demographics of age, education level and gender. In doing so, it has shown that, while some characteristics and qualities do not correlate with one or more of these demographics, this is not typical. For every article trait discussed, at least one demographic correlation was identified with these three demographics.

Understanding what individuals from different backgrounds perceive as important to their news consumption trust decision making is key to ensuring that they are presented with the information that is most relevant to them. This data and analysis, thus, informs efforts to provide online news content consumers, and those that may seek to further share or otherwise use online content, with information that will help them identify deceptive content and take appropriate action, based upon knowledge of what is valued for these purposes by those with similar traits to them.

Identifying the most important information to present to users may be key to developing effective content labeling systems. This knowledge can be used to maximize the use of the available screen space and the potential effectiveness of the label. By developing and evaluating the most effective labels, the efficacy of the labeling paradigm itself can be effectively evaluated to determine if labels in general and specific types of labels are effective at preventing the spread and unintended consumption of fake news content.

Notably, a key limitation of this study is that it is based on respondents predictions of how they would behave in the future, recollections of how they have behaved in the past and perceptions of others' behaviors. Because of this, actual actions that individuals take may differ from these predictions, recollections and perceptions.

Given the foregoing, future work will seek to explore how to best present the demographically-identified relevant information to users. It will also seek to understand if combinations of these and other demographics can be used to better identify what trustworthiness decision information is most valued by users and, thus, provide them with the information that they find most relevant presented in a manner that focuses on the information that the user will find most important. Assessing individuals' actual decisions when making content consumption and label use decisions is also a planned area of future work.

More broadly, this data and analysis also serves to inform a societal conversation regarding preparing individuals to be alert to deceptive content to prevent negative outcomes, such as those discussed in Section 2. Understanding the differences between how individuals of different ages, genders and education levels value different factors in this decision-making helps understand how societal changes over time, education and other socialization factors impact fake news awareness and decision-making. This can be used to drive targeted education initiatives and to define future research efforts.

**Author Contributions:** Conceptualization, J.S. and M.S.; methodology, J.S. and M.S.; resources, J.S.; writing—original draft preparation, J.S. and M.S.; writing—review and editing, J.S., M.S. and B.F.; project administration, J.S.; funding acquisition, J.S.; visualization, B.F. All authors have read and agreed to the published version of the manuscript.

**Funding:** Partial support for this work was provided by the NDSU Challey Institute for Global Innovation and Growth. Funding for the article publication charge was provided by the Hayek Fund for Scholars at the Institute for Human Studies at George Mason University.

**Institutional Review Board Statement:** The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board of North Dakota State University (protocol IRB0003884, approved 23 September 2021).

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Data Availability Statement:** A data release, via a data journal publication, is planned once initial analysis of all data is complete.

**Acknowledgments:** Thanks are given to Jade Kanemitsu from Qualtrics International Inc. for the managemen<sup>t</sup> of the data collection process. Thanks are also given to Ryan Suttle, Scott Hogan and Rachel Aumaugher who developed many of the questions that were used in this study during their earlier work (which was presented in [62]).

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
