Hello my fellow nerdy academics! This is a blog post that will be developing throughout the week. In this post, I'm going to be analyzing the social media platform "Tik Tok" and a couple of controversies surrounding it. As a teaser into those controversies, check out the two short YouTube videos below. More from me soon!
Good evening to my fellow nerdy academics! Tonight's post deals with the concepts of "Social Tagging" and "Bookmarking." As with the earlier post on folksonomies and ontologies, the concepts of social tagging and bookmarking are closely related. Let's jump right in and learn about how social tagging and bookmarking is changing the way we organize information on the web.
In the world of Web 2.0 technology, a user’s ability to interact with information on the web is greater than ever before. Users can use the web to publish their own ideas or interact with others that share a similar interest. Social tagging and bookmarking have become approaches that users can establish access to web-based material and share that access with other users.
Social tagging is the application of tags in an open online environment where the tags of other users are available to others. A folksonomy emerges when users tag content or information, such as web pages, photos, videos, podcasts, tweets, scientific papers and others. Social bookmarking services, on the other hand, allow users to tag, save, manage and share web pages from a centralized source. With emphasis on the power of the community, social bookmarking sites can greatly improves how people discover, remember and share on the Internet.
Social tagging and bookmarking has made classifying, organizing, and sharing bodies of information on the web quite easy. Users are able to navigate, browse, and retrieve information with relative ease. Users not only use tags for the organization of information, but they use them for purely social reasons as well. There are several studies in the literature that seek to understand why people choose to use the tags that they do. Most researchers argue that users use tags to embed themselves in a social environment in order to be watched by others and receive feedback, to assist in the formation of like-minded groups, or to simply make a statement about something that will be publicly accessible.
Again, a folksonomy is formed when a certain tag forms a body of information about a specific topic. When shared with others, or viewed in the context of what others have tagged, these collections of resource identifiers, tags, and people begin to take on additional value through network effects. Searching tags can enable the discovery of relevant resources, and the social relationships that develop among taggers become a means of information discovery in and of themselves.
Social tagging has a number of advantages for the user:
Of course, on the other hand, social tagging has its disadvantages as well:
Social tagging and bookmarking have not only changed the methodology of classification in terms of retrieval information, but it has also changed the way that classifiers organize information. It has removed all concept of hierarchy from the scheme of knowledge organization, facilitating knowledge discovery and web indexing. Proponents of social tagging feel that it reflects the vocabulary and conceptual associations of users making it easier to find information for the average user.
At the end of the day, it will be interesting to see how social tagging and bookmarking evolve with the next major evolution of the Internet. With most all social media sites allowing tagging, large amounts of information can now be classified and searched using these social tags. There is a potential here to revolutionize the way that we conduct social research.
Hello my fellow nerdy academics! I am here again today blogging for an assignment in one of my library classes. Today's post deals with "Metadata Quality Problems." Let's jump right into it...
The assignment was as follows:
After skimming each article below, select one to serve as the focal point for a discussion (~3 - 5 paragraphs posted to your blog or emailed to me) of your impressions of typical metadata quality problems that can occur. (NOTE: I'm more interested in your discussion of the kinds of problems rather than in the specific solutions proposed in these articles):
As for the first problem noted above, the bibliographic data records that libraries receive to accompany e-resources will often be incomplete to meet the library’s need or the data will be inaccurate to match the resource. One way this happens is when the data suppliers send print identifiers with e-resources. The print identifiers are inadequate for e-resources in a variety of ways. One of the most glaring problems with using the bibliographic metadata from a print identifier for an e-resource is that it lacks the 856 tag in the MARC record. Without this 856 tag, there would be no information for the system to provide location and access information to the user. Additional metadata that would be missing would be the format of the digital file, name of the host where the resource is actually being housed, the size of the file, the Uniform Resource Identifier (URI), etc., just to name a few.
Additionally, related to problem number one, even if the bibliographic metadata is available, holdings data can be inaccurate. For example, if a library subscribes to an e-book through any number of data-suppliers, there could be a limit to the number of digital copies of the resource that can be checked out by users at any given time. This is based on the subscription that the library chooses. If the library only allowed for 2 digital copies of a book to be in use at a time, when a user searches for the e-book in the integrated library system (ILS), the results could show that additional downloads are available or that there are no downloads available even if none of the digital copies have been check out. The holdings data is important even with e-resources.
Problem number two noted that bibliographic metadata and holdings data are often not synchronized. When a library subscribes to a new e-resource, data suppliers will often send all of the bibliographic metadata information included in the new subscription first. Then, based on the terms of the contract, the holdings data will come separate. This can often lead to inaccurate holdings data for the e-resources. This is a problem for the user because if the system perceives that the holding limit has been reached for a particular resource, it might not appear in the user’s search.
The inconsistent bibliographic metadata records and holding data being sent separately leads in to the final problem that libraries can often receive data that is in multiple formats. Not all data suppliers adhere to a standard format when providing the bibliographic metadata information. The file formats and the information contained within the file can often be very different than what the library actually needs. When bibliographic metadata arrives that is not accurate, the librarians must spend a significant amount of time making corrections to the data to ensure that the knowledge base has the most correct and updated information available. Another problem here (and with all of the other problems outlined in the article) is that libraries spend a significant amount of time and resources reformatting and completing the data. Of course, when librarians make corrections to the MARC records, a new problem can arise… the possibility of a localized error.
While one might assume that metadata records should be more accurate and easier to incorporate into an ILS than ever, that is certainly not the case. The authors of this particular study are proposing that libraries, service providers, and data suppliers all work more closely together to ensure that the bibliographic metadata records are as accurate as they can be when they arrive at the library.
Hello my fellow nerdy academics! Tonight's post is about two words that, prior to this semester, I really had no experience with. The words are "Ontology" and "Folksonomy." If you didn't know by now, I'm in school earning a Master's of Library and Information Studies at The University of Alabama. So, both of these words deal with how we organize information online...more specifically, within social media. Have you ever used a "hashtag?" If you have, that is a type of folksonomy. A folksonomy is the system in which users apply public tags to online items, typically to make those items easier for themselves or others to find later. Hashtags are a great example of a folksonomy because there are no real rules to classifying information you link to a hashtag. Basically, if you came up with your own hashtag to connect to all of your social media posts (#GriffeysBlogIsAwesome ... for example), then it would allow you to find all of your posts quickly in almost any of our forms of social media that exist today.
An ontology, on the other hand, encompasses a representation, formal naming and definition of the categories, properties and relations between the concepts, data and entities that substantiate one, many or all domains of discourse. All fields develop their own ontologies to reduce the complexity of their data and to organize it in such a way so that it makes sense. In a fascinating article we read for one of the classes that I'm in, the researchers created an ontology related to negative comments posted on Twitter about a compnay's product. By extracting the negative posts associated with the product, it gives the company an opportunity to better understand their consumers' needs. The ontology helps with this process because it helps the researchers pull out important information in a fast and organized way.
While I knew what hashtags were prior to this semester, I was surprised at the level of detail and diversity there is in social tagging. I suppose I knew why people used hashtags, but had never really put too much thought in it beyond an interest in using them for conducting social research (yes...remember, I'm a nerd). With vast amounts of content being created on social media each and every day, finding a way to organize this information is critical and that is where our new vocabulary words come into play - "Ontologies" and "Folksonomies." I hope you have a great week!
Hello my fellow Nerdy Academics! Here is another blog post coming at you. In this blog post I will be discussing a trend in social media that both interests me and disturbs me. That trend is the proliferation of online hate speech. Online hate speech can be defined as a type of online speech, taking place in social media or the internet, that has the purpose of attacking a person or a group on the basis of attributes such as race, religion, ethnic origin, sexual orientation, disability, or gender.
Generally speaking, the concept of “Big Data” in general fascinates me. To offer a simple definition, the term “big data” refers to larger, more complex data sets, especially from new data sources. These data sets are so voluminous that traditional data processing software just can’t manage them. As the Internet has grown and become more complex, the amounts of data collected by everyday users has grown at exponential rates. While there are lots of positive information to be gleaned from big data, I feel that the realization that many of our society’s core problems like racism and sexism are still very much alive and are potentially growing.
On Obama’s 2008 election night, Seth Stephens-Davidowitz discovered that one in every one-hundred Google searches that included the search term “Obama” also included the search terms “KKK’” or the “n-word.” On the same night, he also found that searches for racist websites, most notably the site “Stormfront,” also spiked. If you’re unfamiliar with Stormfront, it is a white nationalist/white supremacist internet forum that openly subscribes to the following values: racism, antisemitism, Holocaust denial, neo-Nazism, and Islamophobia.
For those of you who are unfamiliar him, Seth Stephens-Davidowitz is the author of one of my favorite books of all time, “Everybody Lies.” In the book, Stephens-Davidowitz uses search data from the internet, particularly on Google, social media, dating, and even pornography sites, to paint a fascinating and sometimes grim picture of what is really going on in the minds of everyday people just like you and me. Seth has been able to use “big data” to measure racism, self-induced abortion, depression, child abuse, hateful mobs, the science of humor, sexual preference, anxiety, son preference, and sexual insecurity, among many other topics.
Before moving on to my point, I do want to point out that Stephens-Davidowitz has worked as a data scientist at Google and a visiting lecturer at the Wharton School of the University of Pennsylvania. He is currently a contributing op-ed writer for the New York Times. He received his B.A. in philosophy, Phi Beta Kappa, from Stanford, and his Ph.D. in economics from Harvard.
Now, back to the topic at hand…since 2008, online hate speech has been on the rise with a significant amount being found on social media platforms. Everybody Lies presents some pretty compelling evidence that the increase in online hate speech is certainly a reality. However, beyond just Stephens-Davidowitz’s research, there are other sources in the literature pointing out that this is true. In recent years, most, if not all, of the major social media platforms have said that hate speech is strictly prohibited. The problem is that it is difficult to identify hate speech with so many posts being made each and every day. Much of the hate speech that is caught and removed from various social media sites is reported by other users.
Of course, you may be asking yourself, why is this a problem? We are entitled to free speech aren’t we? These are indeed valid questions for which I will answer both by the end of this post. Let’s start with the first question, why is online hate speech a problem? Online hate speech can be identified as the messages that are spread by white supremacists. White-supremacist groups use social media as a tool to distribute their message with the aim of finding like-minded individuals. When this message reaches certain people, the online messages can turn into real-life violence. Several incidents in recent years have shown that when online hate goes offline, it can be deadly. White supremacist Wade Michael Page posted in online forums tied to hate before he went on to murder six people at a Sikh temple in Wisconsin in 2012. Prosecutors said Dylann Roof “self-radicalized” online before he murdered nine people at a black church in South Carolina in 2015. Robert Bowers, accused of murdering 11 elderly worshipers at a Pennsylvania synagogue in 2018, he had been active on Gab, a Twitter-like site used by white supremacists.
As for the second question, “aren’t we entitled to free speech?,” the short answer is “yes.” However, online hate speech has complicated free speech. Do you think the founders intended for the concept of “free speech” to turn into a platform for alienating and intimidating innocent people? I think most people would argue that that certainly wasn’t their intent. Unfortunately, the founders are not around for us to ask them what they meant. They simply said this, “Congress shall make no law respecting an establishment of religion, or prohibiting the free exercise thereof; or abridging the freedom of speech, or of the press; or the right of the people peaceably to assemble, and to petition the Government for a redress of grievances.” From simply reading the first amendment of the Untied States Constitution, it should be easy to see why it would be difficult for social media platforms and the government to come up with legal ways to manage online hate speech.
I need to be wrapping this blog post up as it is getting a little long winded. I think we need to be more aware than ever at the things people say online. What people say online has real-life consequences. Online hate speech can lead to real-life violence. Cyber-bullying can lead individuals to take their own lives. As academic professionals, we need to do what we can to expose individuals to concepts such as tolerance, acceptance, non-violence, diversity, and multi-culturalism. Helping individuals to understand their similarities with those who might look different than them can help pave the way to a more peaceful and accepting society.
How online hate turns into real-life violence. (2018, November 30). The Washington Post. Retrieved from https://www.washingtonpost.com/nation/2018/11/30/how-online-hate-speech-is-fueling-real-life-violence/
Ruwandika, N. D. T., & Weerasinghe, A. R. (2018). Identification of Hate Speech in Social Media. 2018 18th International Conference on Advances in ICT for Emerging Regions (ICTer), Advances in ICT for Emerging Regions (ICTer), 2018 18th International Conference On, 273–278
Stephens-Davidowitz, S., & Pabon, A. (2017). Everybody lies: Big data, new data, and what the internet can tell us about who we really are. New York: HarperCollins.
Udanor, C., & Anyanwu, C. C. (2019). Combating the challenges of social media hate speech in a polarized society A Twitter ego lexalytics approach. Data Technologies and Applications, 53(4), 501–527.