Biometric Identification Technologies in New Media

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Do you set a password for your laptop, mobile phone, iPad or other electronic devices? If yes, why do you set passwords? I always set up passwords when I receive a new electronic device because I think the equipment provides a private space for me and I want to protect my information on the device. The advance of technology allows me to set up passwords in various ways, from simple words and numbers to biometric recognition, such as fingerprint, voice, and facial recognition.

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Touch ID is a simple way to unlock my iPhone and some Apps. Now, the technology even allows us to unlock the phone with a simple look. For example, iPhone X enables users to unlock their phones by facial recognition. The identification process is based on the algorithm to do a one-to-many search in a database and then reject the faces different from the Phone owner. Since it is difficult for me to remember a lot of passwords for different Apps, touch ID helps me to log in more easily because you will never forget or lose your passwords. Moreover, it helps to improve customer experience. These unique individual characteristics are called biometric features. Using the biometric information to get accesses online, however, worries me. According to Tatham’s report (2017), more and more devices with biometric technology will be produced in the future.

Fingerprints biometrics are becoming the most common identity feature on smartphones… Meanwhile, 93% of top U.S. financial institutions already offer fingerprint scanning in their mobile applications, according to Pascual. According to Acuity Market Intelligence, all smartphones will have at least some kind of biometric technology on board by 2019 and that same growth will extend to wearables and tablets by 2020. (Tatham, 2017, para. 7-8)

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I am concerned where my biometric information stores and who access to my biometric information. Do we only store our data on our phone when we record our fingerprint or voice on the mobile phones? Given that biometric authorization system is a one-to-many matching system, so there must be a database. I believe when we set touch ID or facial recognition to unlock our phones, our information is collected into a database.

Then, is the biometric database legally owned by companies? If the companies own our information, how can they protect our information and keep the database safe? CNBC (March 7, 2017) reported that “[m]ore than 200 apps were found to be exposing sensitive consumer information, with close to 60 percent of the leaks coming from news, sports and shopping apps.” ( When companies are developing biometric identification technology, I think they should think how to secure the database and knowledge the public how safely the information will be protected. It is a part of the corporate social responsibility, and it is a way to meet stakeholders’ expectation of organizational legitimacy.

Of course, protecting individual information is not the only corporate responsibility or the government agenda. We, as users of these new technologies, are responsible for our information. Biometric identifications become a big selling point for technology companies such as Apple Company ( It is appealing to us. However, to protect ourselves, I suggest that the public should know how biometric technology works and what potential issues we will have before using new techniques. In that case, we can safely enjoy new technologies.

Infinite Distraction


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How often do you check your phone a day? I guess, quite often. We check our phones so frequently that we don’t remember how many times we look at our phones a day. According to Apple Company’s report in 2016, “[iPhone] owners unlock their device, on average, 80 times a day.” ( We unlock iPhones to check emails, messages, newest tweets from friends or celebrities, and news happened around the world.


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These infinite distractions from media have captured our attention and distracted us from getting things done. Besides, media distraction may also “‘create a distraction’ so that something else may slip by or remain unconfronted.” (p. 11) The initial impression of distraction on social media reminds me of a Korean TV play I watched several years ago, called Pinocchio (here is the Pinocchio trailer with English subtitle:


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The story begins with a fake report of a fire accident caused the firemen’s death. Ki Ho-sang, the captain of the firefighting squad, died in a factory explosion during a rescue with his team. However, Ho-sang’s body was missing. MSC reporter, Song Cha-Ok, alleged that Ho-sang was still survived and currently hiding because he was responsible for the deaths of his team members. This report caused Ki’s family to become outcasts in their neighborhood and objects of national scorn. Finally, Ho-sang’s wife suicided with her older son (Jae-myeong) by jumping into the sea. Ki Ha-myeong, the little sone, blamed the deaths of his mother and his brother on the media, particularly Cha-Ok’s fake reports. Years later, Ha-myeong became a news reporter, and he finally found out the truth of the fire accident. In order to cover the cause of the fire accident -Company A’s irresponsibility, the MSC reporter create another distraction to shift citizen’s attention.

However, social media distraction discussed in the book Infinite Distraction has mutated. Pettman assumed:

the decoy itself — the thing designed to distract — has merged with the distraction imperative, so that, for instance, news coverage of race riots now distracts from the potential reality and repercussions of race riots. […] This new form of distraction — which acknowledges as much as it disavows — is harder to mobilize against, for the simple reason that no one can accuse “the media” of trying to cover up “the truth.” (p. 11)

Hypermodulation is an essential point Pettman proposed in this book. He described hypermodulation on social media as “deliberate dissonance” to hypersynchronization, a deemed “corporate-governmental control of attention, behavior, and thought.” (p. 29) According to Pettman’s illustration, hypermodulation modulates the order of some pieces of information presenting in front of different users based on personal appetite for distraction. Social media algorithms are similar with hypermodulation to some degree. To my view of point, both algorithm and hypermodulation are based on different individuals’ interests and habits. As a consequence, people “never feel the same way” (p. 29) because they cannot simultaneously access the same material at the same time. One of the benefits of doing so is to reduce the possibility of dangerous surges. Using the information delay or time gap among different users to avoid hazardous surges, the author should think about the length of the time gap. If the time interval of user A and user B seeing the same economic injustice news is two minutes, do you think user A will calm down after two minutes? The emotion caused by the content on social media will last for a while. Probably, both A and B are angry for some time after they see the news and this emotion could transfer into real behaviors. In that case, can we say hypermodulation helps to avoid dangerous surge?


Participatory Culture, Community, and Play: Learning from Reddit


The book Participatory Culture, Community, and Play: Learning from Reddit, written by Adrienne L. Massanari, discusses how participatory culture is created and challenged by both users and designers on Adopting the ethnographic approaches, Massanari provides a detailed investigation of the contradictions within the Reddit’s participatory culture and the impact of geek culture on Reddit.

Participatory Culture

Participatory culture is created by the Internet environment where people can work collaboratively and contact with people who share similar interests. Of course, the preconditions to form the participatory culture is technologies provide users equal opportunities to access the Internet and free to contribute. According to Jenkins et al. (2009, p. xi):

[a] participatory culture is a culture with relatively low barriers to artistic expression and civic engagement, strong support for creating and sharing creations, and some types of informal mentorship whereby experienced participants pass along knowledge to novices. In a participatory culture, members also believe their contributions matter and feel some degree of social connection with one another (at the least, members care about others’ opinions of what they have created).

Benefiting from the technological advance, people have more accesses to the Internet than before. Consequently, the participatory culture has been overgrowing and received unprecedented attention. Furthermore, participatory culture slightly changes the traditional business model and leads us to an age of “sharing economy.” (access on March 18, 2018, at

Theories and Framework

Back to this book, Massanari’s study on Reddit is based on the actor-network theory and activity theory. Both of these two theories are a more theoretical framework and methodologic approach than predictive function. The actor-network theory usually uses to examine the relationships within a network (Simandan, 2017). The activity theory explains how social artifacts mediate social behaviors. Scholars try to understand people’s reactions in a socio-technical system by analyzing the cultural and technical aspects of human behavior (Bertelsen & Bødker, 2003). Typically, six factors will be considered by researchers, including the object, the subject, community, tools, rules, and divisions of labor (the conceptual framework is presented below. More information about the activity system is at


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Based on this framework, Massanari explains the participatory culture on and a series of complex contradictions within the Reddit platform. The most profound part for me is that “how Reddit members and designers espouse a technologically open but discursively closed approach to the community.” (p. 15)

Open or Closed?

Massanari indicates that participatory culture leads to a misunderstanding of women online. In that case, it is difficult for women to participate well in participatory culture. The author adopts geek culture and hegemonic masculinities to explain the phenomenon. There is too much male generated information in the participatory environment, and consequently, such information creates a submissive role for females. Design intent from the male perspective is a central issue in the issue of misunderstanding females online.

Another reason could be a low proportion of female technical workers. Why is the designed from the male perspective? One possible reason is that most of the programmers are males and it is reasonable and convenient for them to build the website from their perspective. I don’t know whether these IT male workers can know women well and design for female users, but females must know females better than males do. Thus, I think technic-related industries should balance their male and female employees.



Bertelsen, O. W., & Bødker, S. (2003). Activity theory. HCI models, theories, and frameworks: Toward a multidisciplinary science, 291-324.

Jenkins, H., Purushotma, R., Weigel, M., Clinton, K., & Robison, A. J. (2009). Confronting the challenges of participatory culture: Media education for the 21st century. MIT Press.

Simandan, D. (2017). Competition, contingency, and destabilization in urban assemblages and actor-networks. Urban Geography, pp.1-12.

Multitasking and Second Screening


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The second screening refers to a second-screen device people are using while they are watching TV. One of the critical advantages of the second-screening behavior is active engagement – people can discuss with people who are watching the same TV programs online when they are watching the programs. Such a real-time communication through the second screen makes individuals feel that they are watching the same screen together. The second-screening behavior not only enhances the discussions among audiences but also makes the real-time interaction between audience and TV programs possible. For example, to keep the audience and make the TV program interesting, China Central Television (CCTV) has collaborated with the most popular social media – Sina Weibo – to interact with the audience during the program. Typically, CCTV will provide a QR code at the corner of the television screen, so people can quickly scan the code with their smartphone or IPad to go to the Sina Weibo page and discuss with others. Or, people can directly use the keywords (e.g., #TV program name, @actors) to join the discussion.

“Two-Screen viewing provides the perfect opportunity for a production to create a wonderful set of immersive experiences for their viewers. As key moments happen on the TV screen, the production can time relevant and extra content to be released directly into their hands (via the second screen), giving the fan access, conversational points and a totally integrated experience.” (Cited in TV & Social Media – The Second Screen, 2016, para. 4, access at

However, do we always consume show-related content on our smartphone or IPad while we are watching TV? I guess most of us do not. According to Rubinson’s research, only 37% of the 7409 participants did nothing when they were watching TV while 45% of audiences were multitasking with a second screen device ( Among the 45% multi-tasking participants, only 6% were consuming show-related content on their second screens. If the data are reliable, I will suspect the effect of the second screen on promoting online engagement.

The related content on the second screen promotes people’s communication online, then, how about the unrelated content on our second screens? The irrelevant information may cause a distraction. Users use smartphone or IPad or other second devices to access separate, unrelated content to multi-task. Why do people do that? Maybe it is a unique habit we have in the digital age. When the content on the primary screen (i.e., TV) is not compelling, the watchers tend to escape from TV to the second screen for unrelated content. This situation makes pressure on content creators and broadcasters to turn this multitasking into a highly compelling experience that can translate into something that advertisers and sponsors care about.

Another question is how the second-screening behavior affects people’s offline participation. According to McGregor and Mourão’s (2017) findings, the mediating role of second screening is decided by viewers’ attitudes. In other words, using the second screen does not have a significant impact on people’s offline behavior. Is attitude the sole variable to affect the offline behavior? Between the content consumption on the second screen and the offline engagement, how many steps further shall we go to connect them?

The second screening research attracts many marketing and advertising scholars, too. They are looking for an appropriate way to do branding as well as to stimulate consumption on the second screen. Unrelated content also can be an opportunity for advertisers to post digital ads (if you are interested in advertising on the second screen, here is the additional information:

Updating to Remain the Same: Habitual New Media

In the book Updating to Remain the Same: Habitual New Media, Chun argues that new media matter a lot, especially when new media become users’ habits and integrate into our daily life. As a consequence, media users become “their machines: they stream, update, capture, upload, share, grind, link, verify, map, save, trash, and troll.” (Chun, 2017, p. 1) Doubtlessly, media are widely used and so powerful. Meanwhile, media blur the bound between “publicity and privacy, gossip and political speech, surveillance and entertainment, intimacy and work, hype and reality.” (p. ix)

The explanations of these positive and negative outcomes are related to new technologies and freedom online. Chun adopts the psychological concept of “habit” as a central point to discuss both dilemmas and opportunities brought by new media in her book. Moreover, she connects habits with networks in the digital age. Chun believes that networks are vital to the dynamics and the imaginary of neoliberalism.

Another thing Chun discusses in her book is the crisis. She thinks that “crisis” is central to the habit and then proposes a formula in her book: Habit + Crisis = Update. Personally, I think this formula means users are always online, so when a crisis happens, they send out information or retweets others’ messages about the crisis. Sometimes, they add comments or add new information. However, the information spread is not powerful enough. Relying on users’ habits online, I think one possible reason why information spread is not robust is that users may just read and continue to scroll their screens. Users are gatekeepers online, too. Thus, information flow will stop in somewhere.

Habit in this book refers to media users are dependent on media, to some degree, and it may become an addiction. The difference between “habit” and “addiction” may present on the degree of the dependency on media. As we discussed at the very beginning of the semester, media addiction is one of the problems of media use. These media habits and addictions are shaped by the media environment. As we discussed last week, various algorithms on social media select specific information or friends for users. Thus, the context the media users exposed has an impact on their habits. Besides, the information flow online cannot reach to each user online because of gatekeepers, non-friending each other, or other reasons. Sometimes, whether a post online will be read by others relies on the capture logic. If the Python does not capture a message, it is hard for users to see the information sometimes. These technical parts are also crucial to habitual new media.

The book moves further to questioning online social practices such as friending and online shaming. Chun argues that social media and the practice of friending lead to a series of gated communities. Users trust these gated communities and ignore the possibility of information leakiness online, which put them in a more dangerous place. As the author mentions before, the media make users hard to differ public and private space. I am concerned about the privacy issues on social media. In the digital age, people are likely to put privacy in an unsafe place. Social media such as WeChat have a function to store personal information and a contact list into WeChat’s iCloud. Users may use that function to upload the data to the iCloud and never realize the possibility of information leakage.

Emerging Media Psychology: Information Processing and Algorithm

What is media psychology? According to American Psychological Association, “media psychology focuses on the psychology behind media and technology use and impact.” ( Media technologies are everywhere and reshape the way we work, live, and communicate. In other words, new media shape media users’ attitudes and even real behaviors. Thus, psychology is the foundation of understanding the impact of new technologies (i.e., new media).

To know how media affects people, there are two main theories. One this the spiral of silence theory and the other one is the dual process theory. The spiral of silence theory proposes that to avoid isolating, people tend to keep silent instead of expressing opposite opinions. Consequently, the majority views become louder while the minority ideas disappear finally. As Neubaum and Krämer (2017) found, people attend the user-generated comments on Facebook to avoid isolation. These comments also serve as public opinion cue to affect readers’ perception of the majority opinion. Based on this theory, I am concerned that whether the media environment kills the diversity of views of the same public issue. The general idea tends to be the majority view finally. Does it hinder the government to understand the real needs or real opinions of the public, consequently lead to unappropriated policy making?

Waddell and Sundar (2017) also explored the influence of comments on people’s attitudes. Specifically, they found that negative comments undermined perceived bandwagon support for the program and reduced enjoyment. Thus, environmental factors such as comments do have the power to shape people’s perceptions.

However, media environment is not the only cue people use to deal with information. People can deal with the message based on personal experience or related knowledge. It is consistent with dual process theory. This theory interprets two possible ways people dealing with information, including central processing route and peripheral route. When an information receiver has personal experience or knowledge of the information he receives, he tends to react to that information based on his experience or knowledge. In this case, when he realizes the information is consistent with his idea, he will show a more strongly positive attitude toward the information. The environmental factors have a weak impact on his opinion or behavior. However, when a receiver has a limited understanding of the information he gets, he prefers to react consistently to the environmental cues he recognizes.

Understanding media psychology is not only a job for researchers or psychologist; many companies are using the knowledge to manage their brands. The significance of social media algorithm is growing. More than content creation, today’s media are integrated with algorithms. All social media platforms run various algorithms behind the screen. Facebook probably is the excellent example of social media algorithm. Given that Facebook is a large platform, too many users there, Facebook aims to tailor different news feed to satisfy different users through running algorithms. Agrawal (2016) pointed out four main factors Facebook uses to decide whether or not a piece of news will appear on your page: 1) the frequency of your interaction with this type of information; 2) the rate of hiding this type of information; 3) the engagement level; and 4) the performance of the post. So, that is why you and I may see the different contents list on our Facebook pages.

Besides, branding posts on social media are well-designed for different groups and different channels. When I worked for a Startup company, the marketing team analyzed the user data each week and decided which contents were suitable for which groups of people. At that time, since we did not have enough budget to collect data, we solely used Google Analytics to understand our audience. For example, we will see at which step we lost the potential clients; which messages attract them more than other information; which area visitors were looking at when they went to our website. After analyzing all the data, the marketing team communicated with the IT team to run different algorithms to achieve the goal. However, sometimes, there was a misunderstanding between the marketing team and IT team.

Algorithms are not the business of IT people; it should be understood by more employees who are not in the technology team. In the future, I think the marketing practitioners and social media specialists are required to grasp some basic knowledge of coding and algorithm to support their daily work. Maybe, agencies or companies will even set new positions about social media algorithm to meet the digital development. If that is the truth, I suggest that students in these areas should learn some intro-level courses about coding, technology, and statistics to equip themselves.

Are social media algorithms always good? Maybe not.




Agrawal, A. (2016). What do Social Media Algorithms Mean for You? Retrieved at on February 25, 2018.

Neubaum, G., & Krämer, N. C. (2017). Monitoring the opinion of the crowd: Psychological mechanisms underlying public opinion perceptions on social media. Media Psychology20(3), 502-531.

Waddell, T. F., & Sundar, S. S. (2017). # thisshowsucks! The overpowering influence of negative social media comments on television viewers. Journal of Broadcasting & Electronic Media61(2), 393-409.

Social Networks and Social Capital

Social media influence the structures of information flow and journalism becomes the most affected industry. Traditionally, the process of news making is controlled by the legacy news organization. However, the emergence of social media allows the public to engage in the news making process, which challenges the “journalists’ editorial autonomy.” (Gans, 1979) Nowadays, the news seems like a collaborative product between journalists and social media users among social media platforms. Specifically, legacy journalism agency still protects its power to report news, but cannot ignore the online users’ engagement and impact on the news. In that case, the meaning of gatekeepers is extended. As Groshek and Tandoc (2016) mentioned, Twitter users choose to tweet, retweet, comment, or share, it is a kind of gatekeeping. It allows the information to flow among different users. To understand why users engage with the messages online, we can also adopt the user and gratification theory to understand the motivations. Given that everyone can be a gatekeeper online, the structure of information flow changes.

Himelboim and his colleagues proposed six structures (i.e., divided, unified, fragmented, clustered, in and out hub-and-spoke networks) of information flow online based on their research on Twitter. I am interested in the in and out hub-and-spoke networks. These two structures are about the centralization, emphasizing the relationship between general users and the hub – a central user – instead of the relationships among the “audience.”

I think these networks are prevalent among the official accounts and their followers on social media. Followers may not know each other, but they all know the brand or the organization they are following. Thus, the engagement always happens between the hub – the official account – and the rest disconnected users. However, these models have a weakness. The participation relies on the hub-spoke. If the official account stops to send messages or update information, the engagement of the followers will decline. Thus, to keep a good relationship with their customers online, I suggest companies actively post messages and interact with their followers online. Since retweets are significant on social media, the content of messages companies post should be well-designed to promote retweet.

No matter using which structure, users build their network online and offline through these online networks. Lu and Hampton (2016) argued that social networks mainly provide social support, including emotional support, tangible aid, and companionship, which serves as motivations for social media utilization. Besides, the use and gratification theory (UGT) explains more why people use the social media and what gratifications people get from it. Different from the social support dimensions proposed by Lu and Hampton’s research, UGT categorizes five motivations: 1) informativeness; 2) entertainment; 3) escape from the real life’s stress; 4) enhance social networks, and 5) identify themselves online. This theory gives us more cues to consider the motivations of users’ engagement and self-disclosure online. For example, when people conduct a campaign, if they can understand the target groups’ needs, it is helpful to influence these target people to the highest potential as well as efficiently grabbing their attention. Understanding the motivations of social media use contributes to the strategic communication online, not only limit to strategic marketing communication, but also health communication, political communication, and other kinds of communication.




Gans, H. (1979). Deciding What’s News (1st ed.). New York: Pantheon Books.

Lu, W., & Hampton, K. N. (2017). Beyond the power of networks: Differentiating network structure from social media affordances for perceived social support. New Media & Society19(6), 861-879.

McQuail, D. (2010). Mass Communication Theory: An Introduction. London: Sage Publications. pp. 420–430.


Affective Publics: Sentiment, Technology and Politics

The book Affective Publics: Sentiment, Technology and Politics, written by Zizi Papacharissi, published in 2014, primarily argues how affection influences digital politics as well as networked publics. Specifically, Papacharissi discusses three cases – the Arab Spring movements, the Occupy movements, and daily trending topics – on Twitter.

Papacharissi extends the meaning of affect by defining it as “the sum of—often discordant—feelings about affairs, public and private, is examined as the energy that drives, neutralizes, or entraps networked publics.” (p. 7) To systematically analyze the affective publics online, Papacharissi utilizes multiple mythologies in her study, including content analysis, network analysis, and textual analysis. These methodologies strengthen her research findings on Twitter’s infrastructure and storytelling affordances.

Affective news on Twitter is storytelling virtually on Twitter. Networked gatekeeping and framing are working together to create the affective news online. Gatekeeping refers to a process to filter information for dissemination. In this book, Papacharissi uses “networked gatekeeping” to describe “crowd-sourced practices permit non-elite and elite actors to co-create and co-curate flows of information.” (Meraz & Papacharissi, 2013; as cited Papacharissi, 2014, p. 48) Besides, framing is a process to enhance the issue prominence in nature. In the context of social media such as Twitter, each user is an information receiver as well as an information sender. So, every user online is co-creating and elevating dominant frames when interacting with others. Through the combined processes of networked gatekeeping and networked framing in the context of social media, opinion leaders emerge, and the dominant frame of a revolution is reinforced.

In that case, public’s affect is guided by the salient issues online and the opinion leaders’ views. Isn’t that another pseudo-environment created by the social media users themselves with stereotypes and biased understanding of facts? Lippmann (1992) believes that the real world is so complicated that people only recognize a pseudo-environment around them, consisting of the images inside their minds. Due to the limited scope of activities, energy, and attention of the outside world, it is impossible for people to know the whole external environment and numerous matters related to them. People comprehend new things they have never experienced through media, such as reading newspapers. The information provided by the press is not a direct reflection of the real environment; instead, it is the pseudo-environment presented by information selection, processing, and restructuring.

Even though we are in the digital age – we absorb a lot of information quickly through social media such as Twitter and Facebook, I think that we still do not understand the world well. Gatekeepers carefully select the information we can receive. The so-called opinion leaders strongly repeat the prominent opinions we can hear. Consequently, the networked publics’ affect could be shaped by the process of gatekeeping and framing.

Papacharissi primarily focuses on the study of Twitter in her book. I suggest that we can expend the research to other social media platforms in the future. Also, affect shapes an individual’s behavior and attitude more or less. The impact of affection should be considered in persuasion area. In addition, since the three cases analyzed in this book are related to the politics or social movement online. When people were talking about the events online, were they free? Was there any censorship of speech in the digital platform during that time? Did different countries perform differently in terms of speech freedom online?



Lippmann, W. (1992). Public Opinion. New York: Harcourt, Brace and Company.

Meraz, S., & Papacharissi, Z. (2013). Networked gatekeeping and networked framing on #Egypt. International Journal of Press/Politics, 18(2), 138–166.

Papacharissi, Z. (2014). Affective Publics: Sentiment, Technology and Politics. Oxford University Press.


Digital Inequalities: Digital Divide and Participation Gap

Scholars are interested in exploring digital inequalities and the reasons for such a phenomenon. Robinson et al. (2015) and Scheerder, van Deursen, and van Dijk (2017) systematically analyzed and generalized three levels of digital divides: The first-level disparities are mainly caused by limited access to the Internet; the second-level gaps are related to skill and efficacy; the third-level digital inequalities focus on the tangible consequences of Internet use. A lot of research has been conducted to explore the first two levels of digital disparities. Now, investigations on the third level are increasing (Scheerder et al., 2017).

The outcomes of Internet use could be diverse. For example, in the business world, the Internet use can influence people’s attitude toward brands and products. In the field of politics, the Internet use may increase people’s political participation and uniform public opinion. This week’s reading provides detailed information on the causes and consequences of digital inequalities.

The Causes of Digital Inequality

The existing studies have found socioeconomic status and sociodemographic such as race, gender, location, and class can predict the online participation. Reisdorf and Groselj (2017) argued that people with low socioeconomic status are more likely to keep away from the Internet using. However, Baym mentioned in her book Personal Connections in the Digital Age that the Internet provides little social cues – there is no way to see other users’ skin color; whether they are health or disable; if they are rich or poor – it makes people feel equal online. If so, doesn’t the Internet promote users a feeling of equality online? Why do people with “socio-economically disadvantaged backgrounds” (Reisdorf & Groselj, 2017, p. 1172) escape from the Internet?

When discussing how digital engagement and participation differ among different users, Robinson et al. (2015) failed to define what “digital engagement” is in their study. Moreover, Robinson et al. (2015) proposed that “Second-level digital inequalities such as those related to skills, participation, and efficacy affect an even greater proportion of the population.” (p. 570) They also mentioned “participation” in the same study. Since “engagement” was mentioned in the first-level digital divide while the concept of “participation” was discussed in the second-level digital divide, I suppose they have different meanings. However, what’s the difference between “engagement” and “participation”? It is confusing. I think the authors should clarify the concepts used in different levels of digital disparities.

Reisdorf and Groselj (2017) explored the role of attitudes toward the Internet in digital inequalities. Not surprising, they found that non-users always hold negative attitudes toward the Internet. It can be explained by the theory of reasoned action (Fishbein & Ajzen, 1975). However, how the negative attitudes related to other factors is still underexplored. Maybe Hoffmann and Meckel’s (2015) study sheds some lights on what causes people’s negative attitudes toward technologies and the Internet. Hoffmann and Meckel (2015) found that self-efficacy and privacy concerns mediate the relationship between sociodemographic and different forms of online participation. I guess that the negative attitudes might be caused by self-efficacy and privacy concerns. Future research is needed to support my hypothesis.

The Consequences of Internet Use

Sasaki (2016) investigated how the Internet use influences people’s online political participation (OPP). Rather than digital inequality, he proposed that internet use equalizes less educated people with well-educated people. Benefiting from using some Internet services, less educated users will generate a positive perception of Internet use. Such a perception let the less educated feel have more power to influence the political process than the educated, which finally could lead the less educated to OPP.

According to Sasaki’s (2016) findings, I suppose that we can find the same results in health communication online. Through using specific types of Internet service, less educated Internet users can feel being equipped with health-related knowledge and also think they can participate the health-related discussion online. In that case, the online environment could help to spread health-related information and promote two-way health communication.

Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley.
Reisdorf, B. C., & Groselj, D. (2017). Internet (non-) use types and motivational access: Implications for digital inequalities research. New Media & Society19(8), 1157-1176.
Robinson, L., Cotten, S. R., Ono, H., Quan-Haase, A., Mesch, G., Chen, W., Schulz, J., Hale, T. M., & Stern, M. J. (2015). Digital inequalities and why they matter. Information, Communication & Society18(5), 569-582.
Sasaki, F. (2017). Does Internet use provide a deeper sense of political empowerment to the Less Educated?. Information, Communication & Society20(10), 1445-1463.
Scheerder, A., van Deursen, A., & van Dijk, J. (2017). Determinants of Internet skills, uses and outcomes: A systematic review of the second-and third-level digital divide. Telematics and informatics, 34(2017), 1607-1624.

Personal Connections in the Digital Age: Digital Media and Society Series

The book Personal Connections in the Digital Age, written by Nancy Baym, describes the role of digital media in the personal relationship. In her book, Baym provides not only examples in our life, but also theories, media-related research, and data to analyze the personal relationship in the context of digital media.

In chapter 2, Baym discusses the consequences of a new medium regarding three perspectives, including technological determinism, the social construction of technology, and social shaping influence. She argues that not only technology changes people’s behavior; people also shape the development of technology. I remembered several days ago Google search engine used Chinese Pinyin to mourn the death of Mr. Youguang Zhou. Mr. Zhou, the father of Chinese Pinyin, created Pinyin by adopting the Latin alphabets. The emergence of Pinyin paves the way for Chinese to communicate online by directly keying in the letters on users’ keyboards. Later, people think that words without social cues limit communication efficiency. People cannot correctly understand the meaning behind the simple words. To make up for that, nowadays, we can use a lot of emoji to express our feelings. Audio and video talking improve the quality of interpersonal communication by presenting non-verbal cues.

The use of digital media causes some problems, too. People worry about the people who are talking with us behind the screen. How much can we trust that person? Since we cannot see and hear others on the Internet, it is a challenge for us to trust other users. However, Baym argues that the Internet is much more credible than we think, and may even be more honest than face to face communication in some cases. “The reduction of social cues would lead to people valuing one another’s contributions for their intrinsic worth rather than the speaker’s status.” (p. 39) I partly agree. I cannot see clear causality between the possibility of liberation from divisions and users’ honesty. Here, the liberation from divisions only influences a user to judge other users’ contribution (if the contribution is the truth) honestly but does not make the user express himself more honestly online.

Another issue we need to notice is that how freely we can speak online. Given that netizens use pseudonyms online and nobody knows who they are, netizens tend to present their opinions unscrupulously online because they believe that they are free – less responsible for their words – in a virtual space. Plus, the First Amendment protects the freedom of public discourse, users’ expressions on digital media may cause some ethical or even legal problems. Can we standard users’ behavior online by improving media law? How to standard it?

Moreover, privacy issue becomes a big concern today. The more we use the digital media, the more others know you. The location presented under my posting tells others where I am; I am worried if the personal information to register my social media account will be disclosed in somewhere; the advertising presented on my Facebook page shows what I just searched on Amazon, etc. The computer and mobile phone know me well. I am concerned who behind the screens know me too much.

This book is informative with a lot of research findings and vivid examples, but some evidence presented in the book may be insufficient to support the author’s view. For instance, in chapter six, Baym argues that the chief goal of using SNSs is to keep the current personal relationships rather than build new relationships. Then, she introduces research about Facebook to support her opinion. The findings show that most of the users’ Facebook “friends” are real friends offline. They know each other in real life before following each other on Facebook. I think the author ignores the features of Facebook when using it as the evidence. To become “friends” on Facebook, two individuals have to confirm the relationship together. In that case, I think people are more likely to send a friend request to somebody they have already known rather than a stranger to get the approval from the person they want to make the relationship. Things may change on SNSs such as YouTube and Weibo. These sites do not require both sides to confirm a connection. Users can follow anybody they are interested in while the followed users cannot add the following people to their friend lists. In that case, I guess the ratio of real friends and strangers in a user’s friend list may change. Thus, I think this is not appropriate evidence to support the author’s idea.