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Proceedings of the3rd European Conference on Social
M di R hMedia Research EM Normandie, Caen, France
12-13 July 2016
Edited byChristine Bernadas and Delphine Minchella
A conference managed by ACPI, UK
Tech Bloggers vs. Tech Journalists in Innovation Journalism
Nirit Weiss-Blatt University of Haifa, Haifa, Israel [email protected] Abstract: The rising power of tech blogs has not gone unnoticed by traditional media professionals, who are aware of the trend that tech blogs often have the upper hand in Innovation Journalism. Countless tech bloggers strive to be the opinion leaders and some journalists praise their supremacy: 'If anybody knows what's going to happen next in technology, it's the bloggers'. The study integrated two research traditions: Two-step flow and agenda setting and focused on the importance of early recognizers who collect, filter and promote the flow of information. The study addressed the question: Do traditional journalists (media agenda) adopt the issue salience assigned by tech bloggers (blogs agenda) or vice versa? In other words, are bloggers the new agenda setters, or is the classic agenda setting model also preserved in the tech field? The core hypothesis was that the salience of tech objects will be transferred from tech blogs to traditional media. The quantitative analyses were conducted in the following steps: 1. The tech agenda of topics discussed in traditional media (# of articles). 2. The tech agenda of topics discussed by tech blogs (# of posts). 3. Spearman rank-order correlation. 4. Time-series analysis (Granger tests for causality). 5. Network Agenda Setting (NAS) model correlations (QAP- Quadratic Assignment Procedure regression analysis). Technological coverage from English-language news and blog posts was collected from all of 2012. 347 keywords were searched in seven groups: 1. Newspaper sites, 2. Television sites, 3. Magazine sites, 4. Websites of traditional media as a whole, 5. Elite newsroom blogs, 6. Independent blogs, 7. Tech blogs as a whole. Approximately 2,500 queries led to 1,500,000 records. The Granger-causality and QAP tests resulted in strong, positive and significant correlations: The tech coverage on blogs predicted the tech coverage on traditional media and not vice versa. Consequently, the tech bloggers were identified as the early recognizers that initiate the classical agenda-setting process to traditional media. It is a unique indication of a role reversal that occurs in the emerging digital era. The study also provided empirical evidence for a new theoretical and methodological development – the NAS model: the relationships between the tech keywords transferred from one communication channel to another. Thus, the salience of the network relationships among objects, in addition to the rank-order of those objects, can also be transferred between different media outlets. Those main findings on the role of tech bloggers in the diffusion of innovation are useful for future studies and also relevant to the industry, including tech companies, PR agencies, tech journalists, and bloggers. Keywords: Agenda setting theory, network agenda setting (NAS) model, two-step flow of communication, innovation journalism, blogs
1. Introduction In the technology landscape, the rising power of tech blogs has not gone unnoticed by traditional media professionals, who are aware of the trend that tech blogs often have the upper hand in the news coverage of this field. The traditional media published articles such as 'the most influential factors on the web' praising the supremacy of the tech bloggers. 'If anybody knows what's going to happen next in technology, it's the bloggers' (Estes, 2011: 2). Thus, this case study of technology coverage examines the idea that countless tech bloggers strive to be the opinion leaders, and some journalists see them as such (Frommer, 2012; Gomes, 2005; McCracken, 2013; Null, 2007; Shani, 2010). Journalism plays a role in innovation ecosystems, and part of the media’s role is to present innovations in a more accessible way to the general public (Nordfors, 2009). Yet journalism’s role in innovation has been barely examined by academic research (Davidson, 2010; Nordfors, 2009). Considering tech bloggers as early recognizers of technological innovation, the study sought to better understand the interplay between the traditional media and tech bloggers in this new media environment.
2. Several observations on the rise of tech blogs 'Bloggers can specialize in particular topics to an extent that few journalists employed by media companies can … a blogger can stick with and dig into a story longer and deeper than the conventional media dare to' (Posner, 2005). In the tech field, the level of 'hands-on' experience and specific expertise matters even more, as the majority of readers do not have technical knowledge or background, and turn to experts for insight. When Clark (2000) determined that 'Geeks Rule!' he explained that the reason for their growing influence is, 'Geeks ‘get’ technology in a time when technology often seems out to get us.' Tech bloggers with a good reputation and a loyal audience of followers have become the new elites in the tech world (e.g., Gomes, 2005; Tippett, 2008; Vaast and Davidson, 2008).
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Harry McCracken (2013), who once worked at PCWorld, stated the following when the magazine became digital-only: 'If you could have shown me the web in 1983, or even 1993, I would have cheerfully traded an infinite number of computer magazines for the chance to read an endless, endlessly diverse quantity of information about tech products, updated not once a month but all day, every day, for free. And today, as much as I once loved computer magazines, I wouldn’t trade TheVerge, Engadget, AllThingsD, ArsTechnica, Daring Fireball, 9to5Mac, ZDNet, TechCrunch and my other favorite tech sites to get them back. The golden age of computer magazines was glorious, but the golden age of computer journalism is now.' In fact, PCWorld was not the only computer magazine that ceased printing issues. PC Magazine (2009), Information Week (2013), and MacWorld (2014) shared the same fate. The new generation of geeks has already become accustomed to the 24/7 online news circle, which contributed to the rise of tech blogs. As examples, LifeHacker, Engadget, and Mashable, each has reached approximately 50 million unique users at the time of writing this paper.
3. Agenda setting and the two-step flow The study integrated two research traditions: agenda setting (McCombs and Shaw, 1972) and the two-step flow of communication (Katz and Lazarsfeld, 1955). In particular, the research drew upon models that bridge the two theories and highlight the importance of early recognizers (Brosius and Weimann, 1996; Weimann and Brosius, 1994). Moreover, the study used the Network Agenda Setting (NAS) model (Guo, 2013; Guo and McCombs, 2011a, 2011b) to examine the associations between objects and whether they are transferred from one communication channel to another.
3.1 Agenda setting The agenda-setting theory’s core proposition is that the salience of elements on the news agenda influences, in turn, their salience on the public agenda. Both the selection of objects for attention and the selection of frames for thinking about these objects are powerful agenda-setting roles. Additional part is called intermedia agenda setting and examines 'who sets the media agenda?' (McCombs and Shaw, 1993). Regarding the influence of blogs on traditional media, the existing research has yielded mixed findings. While some researchers found that the agendas prioritized in blogs had almost no influence on the traditional media (e.g., Gomez-Rodriguez, Leskovec and Krause, 2010), others did find evidence indicating that blogs to some extent set the agenda of traditional news (e.g., Meraz, 2007, 2011; Messner and Garrison, 2011; Wallsten, 2007).
3.2 Network agenda setting model According to the Network Agenda-Setting (NAS) model, not only can the news media tell us 'what to think about' and 'how to think', it might also be able to tell us 'how to link different objects and attributes' to make sense of the world (Vargo et al 2014). The initial studies examined the attributes network (e.g., Guo, 2012); subsequently, both objects and attributes (Chyi and Guo, 2013) and Vu, Guo & McCombs (2014) added the examination of intermedia agenda setting. Prof. McCombs advised (14 May, 2013) that this study will also examine the technological coverage in the NAS model: Therefore, the study also explored the interplay between tech blogs and traditional media from a networked perspective, thus, extended the NAS model to the study of innovation journalism.
3.3 The two-step flow of communication and the role of opinion leaders Brosius and Weimann (1996: 564) defined the role of opinion leaders as 'personal mediators between media and personal agendas' who 'collect, diffuse, filter, and promote the flow of information.' They then proposed four models based on the classical two-step flow theory and agenda setting (see Figure 1).
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Figure 1: Four models of agenda setting and the two-step flow
In this study, bloggers are considered as early recognizers in these models. Tomaszeski, Proffitt and McClung (2014) noted that some blogs are dedicated to responding to the mass media, providing their own interpretations on reported news items (Models 1). Other blogs tend to investigate stories that the mainstream media have not discussed (Models 3 and 4).
4. Research Hypotheses The study started with traditional intermedia agenda-setting hypothesis that the salience of individual tech objects will be positively correlated to each other in different media outlets. H1: The salience of tech-related objects in the traditional media coverage will be positively correlated to object salience in the tech blogs. Covering technological innovations requires special expertise. Therefore, the study expected that tech bloggers disseminate tech issues including scoops, leaks, and rumors, and then the traditional media will adopt. As such, tech bloggers can be considered as opinion leaders that initiate the classic agenda-setting process (see Model 3 in Figure 1). H2. The salience of tech-related objects will be transferred from tech blogs to traditional media. Finally, the study sought to extend the emerging perspective of the NAS Model to the field of innovation journalism. Following the assertion of the basic NAS model, the study hypothesized: H3. The network salience of tech-related objects in the traditional media coverage will be positively correlated to the object network salience in the tech blogs.
5. Method In order to investigate the research hypotheses, a total of 20 websites of traditional news organizations were included in the analysis: 7 newspapers, 6 television news stations and 8 magazines. On the other hand, a total of 30 tech blogs were analyzed: 23 elite newsroom blogs and 7 independent blogs. Appendix A presents a list of the analyzed news media outlets and tech blogs. Technological coverage from these news sites and blogs was collected from January 1, 2012 to December 31, 2012, using the Big Data analysis tool Media Analysis Platform (MAP) provided by the company Sysomos/MarketWire. Lists of keywords that indicate different tech-related topic categories—tech companies, tech products, tech themes, tech industry events and tech leaders— were generated using several sources that summarize major tech stories, including 'Techmeme’s biggest stories of the year' (2008–2012). This inductive process resulted in a total of 347 keywords. A sample of 20% from these keywords was selected for intercoder reliability testing on the use of a keyword as an indicator of a particular tech category. Between three different coders, the results were satisfactory: Fleiss’ Kappa: 82.2; Cohen’s Kappa: 82.2; Krippendorff ’s Alpha: 82.3.
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Each keyword was then used to retrieve relevant tech stories from seven different media groups: (1) newspaper sites, (2) television sites, (3) magazine sites, (4) websites of traditional media as a whole, (5) elite newsroom blogs, (6) independent blogs, and (7) tech blogs as a whole. The first round of analysis was based on the frequency counts of the keywords. Specifically, the agenda of tech-related topics discussed in the traditional media was measured by the number of news articles that mentioned the selected keywords. The agenda of tech-related topics discussed in tech blogs was measured by the number of blog posts that mentioned the keywords. In investigating H1, Spearman’s rank-order correlation tests were conducted to explore the degree of correlation between the traditional media’s agenda and the tech blog’s agenda with respect to each of the three main categories: high-tech companies, high-tech products, and tech-related themes. H2 asked about the direction of the intermedia agenda-setting relationship between the traditional media and tech blogs. The Granger (1969) causality test was used to investigate this hypothesis. Specifically, the test compares the effect of one time series on another in order to verify the causal direction between the two time-bound variables (Yanovitzky and VanLear, 2008). A growing number of agenda-setting and intermedia agenda-setting studies (e.g., Meraz, 2007; Rojecki and Meraz, 2014; Sayre et al 2010) used Granger causality tests as a time-series analytic technique. Compared to other techniques, such as time-lagged correlations and ARIMA modeling, Granger causality testing has been found to be more accurate, and it can provide clearer evidence of time-order relationships (Groshek and Clough-Groshek, 2013; Meraz, 2011). In Granger causality tests, an appropriate time lag must be selected. Most studies rely on statistical criteria such as Akaike’s information criterion (AIC) (Groshek and Clough-Groshek, 2013). In this analysis, an optimal lag length was determined for an unrestricted VAR model for a maximal lag length of 30 days, using AIC as criteria. Then the VAR model was applied to the data using the order of the model that showed lowest AIC on the previous step. The hypothesis of Granger causality was tested using an F test, and significance was estimated by a bootstrapping procedure with 5,000 boots to ensure the robustness of the findings. Finally, in order to examine the NAS model (H3), a network analysis was conducted to explore the co-occurrences of leading keywords that indicate tech companies, tech products, and tech themes. Any two keywords that appeared in the same news headline were counted as a co-occurrence. The matrices do not include the appearance of two keywords in the full articles/posts, due to the huge database (1.5 million records) which would have generated tens of thousands of matches, some of which could have been random. Quadratic Assignment Procedure (QAP) was then used to examine the degree of correlation between the tech agendas from a networked perspective. UCINET 6 was used to conduct network analysis (Borgatti, Everett and Freeman, 2005), and NetDraw 2.0 (Borgatti, 2002) was used to visualize the results.
6. Results The study focused on the leading keywords (the top fifty or top thirty in each category). Table 1 summarizes the top five keywords in the main tech categories highlighted by the traditional media and tech blogs, respectively.
Table 1: A summary of top five keywords in the different media outlets
#5#4#3#2#1RankingTech companies
Samsung Twitter Facebook Google Apple Blogs Samsung Microsoft GoogleAppleFacebookTraditional Media
Tech productsMac iOS iPad iPhone AndroidBlogs
Windows 8iOS AndroidiPadiPhoneTraditional MediaTech topics/themes
Gadgets Software Tablets Smartphones Apps Blogs TabletsSmartphonesSocial Media AppsSoftwareTraditional Media
In addressing H1, Figure 2 presents the results of Spearman’s rank-order correlations tests. Strong, positive and significant correlations were found between the traditional media and the blogs. The strongest media-blog correlation was found about the agenda of tech products (0.91), followed by tech themes (0.70) and companies (0.68). Strong, positive and significant correlations also were found between sub-groups within each category (e.g., newspapers vs. television networks); and between sub-groups in different categories (e.g.,
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elite newsroom blogs vs. newspapers, independent blogs vs. magazines). Overall, the study found that different media outlets reached a consensus about which tech topics to cover. Both the traditional media and tech blogs agreed on what counted as newsworthy in the tech field.
Figure 2: Spearman rank-order correlations between traditional media and tech blogs. Categories: Tech companies, tech products, tech themes
H2 examined the direction of intermedia agenda-setting relationship between the traditional media and tech blogs. The first analysis reveals that the independent variable in the equation 'Granger-caused' the dependent variable. That is, the tech coverage on the blogs Granger-caused the tech coverage on the traditional media (F = 2.99 - 5.78, p < 0.05). In other words, tech blogs primarily led traditional media coverage of technology. The results of the second analysis were not statistically significant (p > 0.05), thus, the tech coverage on traditional media did not explain the tech coverage on blogs. Similarly, in the regression tests, the difference between the models was considerably larger in the direction of blogs coverage explaining traditional media coverage. Thus, blogs have a more significant contribution as predictors, unlike the reversed direction. Tables 2 and 3 summarize the Granger causality test results.
Table 2: Granger tests comparing blogs coverage of leading tech companies/ products/theme to traditional media coverage
Granger-causality Tech Blogs to Traditional MediaIssue Vectors
(Tech coverage) Regression with
Traditional history R2 Regression with Traditional + Blogs
history R2R2
change F-stat Significance
(P-value)Apple 0.31 0.56 0.25 2.99 0.004
Google 0.43 0.69 0.26 5.01 0.003 Samsung 0.37 0.62 0.25 3.74 0.005 Microsoft 0.45 0.70 0.25 4.41 0.0004 Android 0.50 0.69 0.19 4.47 0.0002
iOS 0.42 0.57 0.15 5.78 0.001 Privacy 0.29 0.40 0.11 4.42 0.001
Note: All statistical tests from tech blogs to traditional media are significant (p < 0.05).
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Table 3: Granger tests comparing traditional media coverage of leading tech companies/ products/theme to blogs coverage
Granger-causality tests Traditional Media to Tech Blogs
Issue Vectors (Tech coverage)
Regression with Blogs history R2
Regression with Blogs + Traditional history R2
R2
change F-stat Significance
(P-value)Apple 0.51 0.58 0.07 1.64 0.175
Google 0.63 0.76 0.13 1.83 0.128 Samsung 0.58 0.66 0.08 1.87 0.169 Microsoft 0.54 0.66 0.12 1.01 0.432 Android 0.53 0.62 0.09 1.06 0.483
iOS 0.62 0.70 0.08 1.82 0.117 Privacy 0.40 0.48 0.08 1.78 0.094
Note: All statistical tests from traditional media to blogs are not significant (p > 0.05).
To examine the NAS model, a network analysis was conducted to operationalize the links between different objects in the traditional media and tech blogs coverage, respectively. Matrices based on these links were then created to represent the networked agendas in different media outlets. Specifically, tech keywords that appeared together in the same news headline were considered as connected with each other. In addressing H3, the QAP analysis revealed strong and significant correlations between the traditional media and tech blogs at the network level: tech themes (r=0.77, p=0.005), tech companies (r=0.92, p<0.001) and tech products (r=0.74, p=0.03). In other words, the way in which the tech bloggers associated different keywords in covering tech news was found significantly similar to that in the traditional media.
As an example, Figure 3 visually represents how the traditional news sites and tech blogs associated different tech-related keywords in their tech coverage. The more frequently the two items co-occurred in the same headlines, the stronger their connection. Accordingly, the thicker the line is in the graph, the stronger the relationship between the two corresponding nodes. Focusing on pairs of keywords and as well as the entire networks of different nodes make it possible to discover more details about the news coverage. For example, the keyword associations as reflected in Figure 3 did not necessarily match the general ranking of individual products on the hierarchical media agendas.
Figure 3: Network visualization: Tech products vs. rumors
7. Discussion By conducting a series of analysis, the study found strong, positive and significant correlations between the traditional media and tech blogs in their coverage of technological innovations. Importantly, the results demonstrate that the tech coverage on blogs Granger-caused the tech coverage on traditional media, and not vice versa. In other words, tech bloggers activity was found as a strong and significant predictor of the tech coverage by traditional tech journalists, unlike the reversed direction. Thus, the traditional media appeared to follow tech blogs in covering different aspects of tech-related news. It is a unique indication of a role reversal that occurs in the emerging digital era. A set of interviews with some of the leading tech bloggers offered an explanation, the bloggers stated that: The intense publishing; the ability to make use of specific expertise and to dig deeper than conventional media; the opinionated and personal writing style; and focusing on early stage technology startups (Alpha/Beta) - makes them the professional platform for tech initiatives. Another explanation suggested was that traditional media use quotes like "according to tech blog" in order to avoid risking their reputation if the
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story does not develop as expected or if it's a rumor. The bloggers stated that they are not afraid to publish rumors as long as they are disclosed as rumors. In addition to exploration of hierarchical media agendas (rank-order of objects), the results based on QAP tests reveal that the patterns of network relationships between different tech objects were found similar in blogs and traditional media. The network analysis specified the linkages between different tech issues, and the findings support the NAS Model in the sense that bundles of elements can be transferred from one communication channel to another, thus, providing a richer depiction of the intermedia agenda-setting effects. This study focused on the issue salience. It is recommended that future research will further examine the issue attributes (positive/negative/neutral).
8. Conclusions What is the role of tech blogs in the flow of information? Tech bloggers observe the field through a variety of sources such as tech companies and public relations agencies. They filter tech issues and their interrelationships, and may even set the traditional media’s agenda, which in turn will transfer the salience of these topics and their associations to the general public. Consequently, we can consider tech blogs as early recognizers or opinion leaders of technological innovations, which perhaps can be best illustrated in Model 3 (see Figure 1). Tech companies and their PR firms, when looking how to best promote their tech agenda, may benefit from the main conclusion of this research. The tech bloggers were found to be the trendsetters of the tech coverage and thus, they are recommended as an efficient channel for the flow of innovative information in the tech field. Another observation based on the findings is 'The power law' (e.g., Shirky, 2003) as manifested in the tech field: A few topics achieved the majority of the coverage and all others got a considerably lower coverage. A condition of winners-take-all was found across the different categories (e.g., tech companies/products rankings). Thus, the findings point out a possible phenomenon of 'pack journalism' (Crouse, 1973 in Weaver, McCombs and Shaw, 2004), which occurs in intermedia agenda setting: agreement on what is newsworthy. In addition, the majority of news articles and posts dealt with products being launched (software or hardware). However, other potentially important tech-related topics such as 'censorship,' 'cyber security' and privacy issues were not salient in the coverage during the sampled time period. Furthermore, in the coverage timelines of the big brands, although there were interesting negative stories regarding failures, layoffs or investigations, they drew considerably less interest. A possible explanation is that big tech companies might spend billions of dollars on marketing campaigns. Overall, this study contributes to the theoretical discussion around the future of mass communication research in the new media era. Following Chaffee and Metzger’s (2001) article 'The End of Mass Communication?' Weimann et al (2014: 822) asserted that 'old communication theories never die; they just readjust.' In accordance with this assertion, the current study suggests that the four models of information flow are still relevant today, particularly in the field of innovation journalism.
References Borgatti, S.P. (2002) NetDraw: Graph visualization software, Cambridge, MA: Analytic Technologies. Borgatti, S.P., Everett, M.G. and Freeman, L.C. (2005) UCINET 6 for Windows, Cambridge, MA: Analytic Technologies. Brosius, H.B. and Weimann, G. (1996) 'Who sets the agenda? Agenda-setting as a two-step flow', Communication Research,
vol. 23, pp. 562–581. Chaffee, S.H. and Metzger, M.J. (2001) 'The end of mass communication?', Mass Communication and Society, vol. 4, no. 4,
pp. 365–379. Chyi, H.I. and Guo, L. (2013) 'The pictures of China in our heads: Mapping China on Taiwan's network media agenda, 1987-
2011', Paper presented at the 63th Annual Conference of the International Communication Association (ICA), London, England.
Clark, C.J. (2000) Geek learning: The benefits of discovering your inner geek. Caleb Clark’s Site. Available: https://calebjc.files.wordpress.com/2015/03/geek_learning.pdf
421
Nirit Weiss-Blatt
Davidson, E. (2010) 'Tech talk: Investigating the emergence of new actors through new media in technology innovation discourse' Information Systems Research Seminar, Department of Information, Operations & Management Sciences, NYU Stern School of Business, NY, USA. Available: http://web-docs.stern.nyu.edu/old_web/emplibrary/ElizabethDavidsonSp2010.pdf
Estes, A.C. (2011) 'The tech blogger bubble is here', The Atlantic Wire. Available: http://www.theatlanticwire.com/business/2011/10/tech-blogger-bubble-here/43275/
Frommer, D. (2012) 'Rise of the tech bandits', SAY Magazine. Available: http://saymedia.typepad.com/_pdf/SAY-Magazine-Summer2012-download.pdf
Gomes, L. (2005) 'Tech blogs produce new elite to help track the industry’s issues', The Wall Street Journal. Available: http://online.wsj.com/articles/SB113391812858915737
Gomez-Rodriguez, M., Leskovec, J. and Krause, A. (2010) 'Inferring networks of diffusion and influence', KDD ’10- Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA.
Granger, C.W. (1969) 'Investigating causal relations by econometric models and cross-spectral methods', Econometrica: Journal of the Econometric Society, vol. 37, no. 3, pp. 424–438.
Groshek, J. and Clough-Groshek, M. (2013) 'Agenda trending: Reciprocity and the predictive capacity of social network sites in intermedia agenda setting across issues over time', SSRN Electronic Journal, Available: http://papers.ssrn.com/sol3/papers. cfm?abstract_id=2199144
Guo, L. (2012) 'The application of social network analysis in agenda setting research: A methodological exploration', Journal of Broadcasting & Electronic Media, vol. 56, no. 4, pp. 616-631.
Guo, L. (2013) Toward the third level of agenda-setting theory: A network agenda-setting model. In T. Johnson (ed.) Agenda setting in a 2.0 world: New agendas in communication, pp. 112–133, New York, NY: Routledge.
Guo, L. and McCombs, M. (2011a) 'Network agenda setting: A third level of media effects', Presented at the International Communication Association (ICA) annual conference, Boston, MA, USA.
Guo, L. and McCombs, M. (2011b) 'Toward the third level of agenda-setting theory: A Network Agenda Setting Model' Presented at the Association for Education in Journalism and Mass Communication annual conference, St. Louis, MO, USA.
Katz, E. and Lazarsfeld, P.F. (1955) Personal influence: The part played by people in the flow of mass communications, Glencoe, IL: Free Press.
McCombs, M.E. and Shaw, D.L. (1972) 'The agenda-setting function of mass media', Public Opinion Quarterly, vol. 36, no. 2, pp. 176–187.
McCombs, M.E. and Shaw, D.L. (1993) 'The evolution of agenda-setting research: Twenty-five years in the marketplace of ideas', Journal of Communication, vol. 43, no. 2, pp. 58-67.
McCracken, H. (2013) 'PCWorld exits print, and the era of computer magazines ends', TIME. Available: http://techland.time.com/2013/07/11/pcworld-exits-print-and-the-era-of-computer-magazines-ends/
Meraz, S. (2007) The networked political blogosphere and mass media: Understanding how agendas are formed, framed, and transferred in the emerging new media environment. Dissertation Abstracts International Section A: Humanities and Social Science, 68(12-A), Available: http://gradworks.umi.com/32/91/3291292.html
Meraz, S. (2011) 'The fight for ‘how to think’: Traditional media, social networks, and issue interpretation', Journalism, vol. 12, no. 1, pp. 107–127.
Messner, M. and Garrison, B. (2011) 'Study shows some blogs affect traditional news media agendas', Newspaper Research Journal, vol. 32, no. 3, pp. 112–126.
Nordfors, D. (2009) 'Innovation journalism, attention work, and the innovation economy. A review of the innovation journalism initiative 2003–2009', Innovation Journalism, vol. 6, no. 1, pp. 1–46.
Null, C. (2007) 'The 50 most important people on the web', PCWorld, Available: http://www.pcworld.com/article/129301/article.html?page=0
Posner, R.A. (2005) 'Bad news', New York Times, Available: http://www.nytimes.com/2005/07/31/books/review/bad-news.html?_r=0
Rojecki, A. and Meraz, S. (2014) 'Rumors and factitious informational blends: The role of the web in speculative politics', New Media & Society [Published online], Available: http://nms.sagepub.com/content/early/2014/05/16/1461444814535724. abstract
Sayre, B., Bode, L., Shah, D., Wilcox, D. and Shah, C. (2010) 'Agenda setting in a digital age: Tracking attention to California Proposition 8 in social media, online news and conventional news', Policy & Internet, vol. 2, no. 2, Article 2.
Shani, R. (2010) 'The most influential factors on the web', Yedioth Acharonot- Mamon, p. 8–9. [Hebrew]. Shirky, C. (2003) 'Power laws, weblogs, and inequality' in M. Ratcliffe and J. Lebkowsky (eds.), Extreme Democracy, 46-52,
Available: http://www.shirky.com/writings/powerlaw_weblog.html Tippett, M. (2008) 'The most public index, Silicon Valley', NowPublic, Available: http://socialmedia.biz/2008/08/02/silicon-
valleys-top-50-web-influencers/ Tomaszeski, M., Proffitt, J. M. and McClung, S. (2014) 'Exploring the political blogosphere: Perceptions of political bloggers
about their sphere', Atlantic Journal of Communication, vol. 17, no. 2, pp. 72–87. Vaast, E. and Davidson, E. (2008) 'New actors and new media in technology discourse: An investigation of tech blogging',
Proceedings of the International Conference on Information Systems (ICIS), Paris, France. Paper 162.
422
Nirit Weiss-Blatt
Vargo, C., Guo, L., Shaw, D. and McCombs, M. (2014) 'Network issue agendas on Twitter during the 2012 U.S. presidential election', Journal of Communication, vol. 64, no. 2, pp. 296-316.
Vu, H.T., Guo, L. and McCombs, M.E. (2014) 'Exploring "the world outside and the pictures in our heads". A network agenda-setting study', Journalism & Mass Communication Quarterly, vol. 91, no. 4, pp. 669-686.
Wallsten, K. (2007) 'Agenda setting and the blogosphere: An analysis of the relationship between mainstream media and political blogs', RPR—Review of Policy Research, vol. 24, no. 6, pp. 567–587.
Weaver, D., McCombs, M.E. and Shaw, D.L. (2004) 'Agenda-setting research: Issues, attributes, and influences' in L.L. Kaid (ed.), Handbook of political communication research, Mahwah, NJ: Lawrence Erlbaum Associates.
Weimann, G. and Brosius, H.B. (1994) 'Is there a two-step flow of agenda-setting?', International Journal of Public Opinion Research, vol. 6, pp. 323–341.
Weimann, G., Weiss-Blatt, N., Mengistu, G., Mazor, M. and Oren, R. (2014) 'Reevaluating "The End of Mass Communication?"', Mass Communication and Society, vol. 17, no. 6, pp. 803–829.
Yanovitzky, I. and VanLear, A. (2008) 'Time series analysis. Traditional and contemporary approaches' in A.F. Hayes, D., Slater and L.B. Snyder (eds.), The SAGE sourcebook of advanced data analysis methods for communication research, pp. 89–124, Thousand Oaks, CA: Sage.
Appendix A Twenty websites of traditional media
Seven newspapers New York Times; Washington Post; USA Today; LA Times; Wall Street Journal; Chicago Tribune; San Francisco Chronicle—SFGate.com
Five TV stations CNN (U.S. Edition); NBC News (at MSNBC); FOX News; ABC News; CBS News
Eight magazines ComputerWorld; PCWorld; InfoWorld; MacWorld; NetworkWorld; Wired; PC Mag; InformationWeek Thirty tech blogs
Twenty-three elite newsroom blogs (A-list) 9TO5Mac; AllThingsD; Android Authority Blog; Android Community; ArsTechnica; Bits; BoingBoing; Engadget; Geek.com; Geeky-Gadgets; GigaOm; LifeHacker; MacRumors; Mashable; ReadWrite; SlashGear; TechCrunch; TechDirt; TheNextWeb; TheVerge; TUAW-The Unofficial Apple Weblog; ubergizmo; WMPowerUser
Seven independent bloggers Amit Agarwal Digital Inspiration; Daring Fireball—John Gruber; John Battelle’s Search Blog; Krebs on Security; Scripting News—Dave Winer; Scobleizer; Scott Hanselman’s Computer Zen
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