User:Josh.munson/sandbox

Jessica's Peer-Review

Hi Josh, apologies on the delayed Peer_review on your content within your sandbox. I was working with Shalor from Wikipedia and he recommended that I work directly to provide feedback on your page. Here are some observations/initial reactions on the Impression Management topic. Please feel free to request additional feedback or let me know if you have any questions.

• Agree that overall most of the content in the article is pretty well written and that minor grammatical changes are all that is needed.
• I would recommend that there are some additional references/resources added to the article to ensure that the readers are able to lean on other content.
• Perspective is neutral and is not one sided so definitely includes some balance for the reader.
• Also make good links within Wikipedia articles and difference users.

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Week 2: Article evaluation

I decided to read the Wikipedia page about my hometown, Selah, WA. Some thoughts:

• I felt the tone was very neutral. It wasn't written with a tone to convince people to visit the city or promote tourism. I was surprised when I read the Talk page that a user had deleted a sentence from the article because it was a negative comment about a nearby city. This reinforced the neutral tone because there was no need for the negative, opinionated comment on the page.
• The talk page was pretty limited with comments. One user asked a great question of how to properly pronounce the city's name. I am going to look for a strong source to add this information to the article.
• The article essentially only reports on the 2000 and 2010 census. I feel like there are other areas that the article could educate readers on (i.e. history, economy, agriculture, etc.).
• The sources for the article all seem relevant. I would add The Selah Story by Robert S. Lince (although the article does suggest this book for further reading) as a source on any of the town's history and I would also pull information from the city's government website.

Week 3: Article Evaluation

I selected the article about the filter bubble. Some thoughts:

• Talk page: The talk page had many detailed comments and suggestions on it. It appears that this article is used as a project in many different communication-focused academic courses because there were many student postings evaluating it on the same criteria as I am here. While reading through the comments, I gained a better perspective on what the term filter bubble means, as well as recommendations on how it should be presented on its Wikipedia page. Based on the feedback on the Talk page, some areas of improvement that I may look into are checking the linked sources to make sure links aren't broken, do research on the sources and make sure there are a variety of sources to ensure neutrality, and check the different headings and make sure some sections aren't over-developed or under-developed.
• Tone: The tone was very neutral. A comment in the Talk page referenced how the individual felt the tone was leaning heavily to how the filter bubble is a negative effect. It makes me wonder if that individual went back through and did some editing because I did not feel that tone while I was reading through the article. I can, however, see their point on how it can be negative. I felt the article also had an academic tone to it. While reading through it, I genuinely learned concepts I was unaware of prior to this assignment.
• Sources: This article uses a lot of sources and a lot of direct quotes. For a relatively small article, there are 96 sources. I'd be curious to learn what the "industry standard" is for a Wikipedia article. I also noticed their punctuation after a direct quote (comma, period, etc.) fall outside of the quotation marks, not inside. This is a grammatical change I will edit. After clicking through a handful of the sources and scanning the majority of them, they all seem relevant and are dated within the last 2-3 years. I do question how some sources are from articles such as the Huffington Post, and I'd like to see the references be from more reliable academic sources. That may be something to dive into.
• The similar concepts and the dangers of filter bubbles sections seem a little under developed to me. I am also curious about diving into the causes and effects of filter bubbles. These might be areas of focus.

Sources for Further Research

Allred, K. (2018, Apr 13). The causes and effects of filter bubbles and how to break free. Medium.com. Retrieved at https://medium.com/@10797952/the-causes-and-effects-of-filter-bubbles-and-how-to-break-free-df6c5cbf919f.

How filter bubbles distort reality: Everything you need to know. Farnam Street. Retrieved at https://fs.blog/2017/07/filter-bubbles/.

Leetaru, K. (2017, Dec 18). Why 2017 was the year of the filter bubble? Forbes.com. Retrieved at https://www.forbes.com/sites/kalevleetaru/2017/12/18/why-was-2017-the-year-of-the-filter-bubble/#6b071d41746b.

Pariser, E. (2011, Mar) “Beware online 'filter bubbles.'” TED: Ideas worth spreading. Retrieved at https://www.ted.com/talks/eli_pariser_beware_online_filter_bubbles.

The isolating web: Do filter bubbles narrow down our mind. Boston University. Retrieved at https://sites.bu.edu/cmcs/2018/12/06/the-isolating-web-do-filter-bubbles-narrow-down-our-mind/.

Edits

Copied from Filter bubble:

The term was coined by Internet activist Eli Pariser circa 2010 and discussed in his 2011 book of the same name; according to Pariser, users get less exposure to conflicting viewpoints and are isolated intellectually in their own informational bubble. He related an example in which one user searched Google for "BP" and got investment news about British Petroleum, while another searcher got information about the Deepwater Horizon oil spill, and noted that the two search results pages were "strikingly different."

Pariser defined his concept of a filter bubble in more formal terms as "that personal ecosystem of information that's been catered by these algorithms." An Internet user's past browsing and search history is built up over time when they indicate interest in topics by "clicking links, viewing friends, putting movies in [their] queue, reading news stories," and so forth. An Internet firm then uses this information to target advertising to the user, or make certain types of information appear more prominently in search results pages. This process is not random either, and it operates under three step process. According to Eli Pariser's book, the process states, "First, you figure out who people are and what they like. Then, you provide them with content and services that best fit them. Finally, you tune to get the fit just right. Your identity shapes your media." This portrays how we are allowing the media to formulate our thoughts because of the repeated messages we encounter daily.

Below are edits to the section Profiles on Social Networking Sites on the Impression Management Wiki page:

• The section of the article truly did not need a whole lot of editing. I mainly just made a few grammar fixes: I made a few sentences active instead of passive, added some commas, and moved punctuation inside quotation marks.

Below are my thoughts on how the article rates when compared to Wiki's top 5 elements:

• A lead section: The lead wasn't necessarily strong, but it gets the job done. It covered the history of impression management, however I would like to see it include what that means today, especially since we are in the prime of the digital age.
• A clear structure: The structure is chronological and makes sense to me as a reader. It moves from the inception of impression management, to theories, to modern-day application.
• Balanced coverage: The article seemed very balanced. I especially wanted to compare the theories portion to the application portion. The two topics had equal coverage.
• Neutral content: The article had a neutral voice. Information did not seem biased and instead felt very reliable.
• Reliable sources: Overall, the sources seemed to primarily be reliable. I did not see any magazine or blog articles used, and there was a high usage of academic journals or articles cited.