Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

May 9, 2015

Exposure to Diverse Information on Facebook [Skepticism]

Filed under: Facebook,News,Opinions,Social Media,Social Networks,Social Sciences — Patrick Durusau @ 3:06 pm

Exposure to Diverse Information on Facebook by Eytan Bakshy, Solomon Messing, Lada Adamicon.

From the post:

As people increasingly turn to social networks for news and civic information, questions have been raised about whether this practice leads to the creation of “echo chambers,” in which people are exposed only to information from like-minded individuals [2]. Other speculation has focused on whether algorithms used to rank search results and social media posts could create “filter bubbles,” in which only ideologically appealing content is surfaced [3].

Research we have conducted to date, however, runs counter to this picture. A previous 2012 research paper concluded that much of the information we are exposed to and share comes from weak ties: those friends we interact with less often and are more likely to be dissimilar to us than our close friends [4]. Separate research suggests that individuals are more likely to engage with content contrary to their own views when it is presented along with social information [5].

Our latest research, released today in Science, quantifies, for the first time, exactly how much individuals could be and are exposed to ideologically diverse news and information in social media [1].

We found that people have friends who claim an opposing political ideology, and that the content in peoples’ News Feeds reflect those diverse views. While News Feed surfaces content that is slightly more aligned with an individual’s own ideology (based on that person’s actions on Facebook), who they friend and what content they click on are more consequential than the News Feed ranking in terms of how much diverse content they encounter.

The Science paper: Exposure to Ideologically Diverse News and Opinion

The definition of an “echo chamber” is implied in the authors’ conclusion:


By showing that people are exposed to a substantial amount of content from friends with opposing viewpoints, our findings contrast concerns that people might “list and speak only to the like-minded” while online [2].

The racism of the Deep South existed in spite of interaction between whites and blacks. So “echo chamber” should not be defined as association of like with like, at least not entirely. The Deep South was a echo chamber of racism but not for a lack of diversity in social networks.

Besides lacking a useful definition of “echo chamber,” the author’s ignore the role of confirmation bias (aka “backfire effect”) when confronted with contrary thoughts or evidence. To some readers seeing a New York Times editorial disagreeing with their position, can make them feel better about being on the “right side.”

That people are exposed to diverse information on Facebook is interesting, but until there is a meaningful definition of “echo chambers,” the role Facebook plays in the maintenance of “echo chambers” remains unknown.

August 13, 2012

Summarize Opinions with a Graph – Part 1

Filed under: Graphs,Neo4j,Opinions — Patrick Durusau @ 4:36 pm

Summarize Opinions with a Graph – Part 1 by Max De Marzi.

From the post:

How does the saying go? Opinions are like bellybuttons, everybody’s got one? So let’s say you have an opinion that NOSQL is not for you. Maybe you read my blog and think this Graph Database stuff is great for recommendation engines and path finding and maybe some other stuff, but you got really hard problems and it can’t help you.

I am going to try to show you that a graph database can help you solve your really hard problems if you can frame your problem in terms of a graph. Did I say “you”? I meant anybody, specially Ph.D. students. One trick is to search for “graph based approach to” and your problem.

I’ll give you an example. The other day I ran in to “Opinosis: A Graph Based Approach to Abstractive Summarization of Highly Redundant Opinions” by Kavita Ganesan, ChengXiang Zhai and Jiawei Han at the University of Illinois at Urbana-Champaign.

I think you are going to like this. Max’s work is always interesting but this post is particularly so.

Has implications beyond opinion gathering.

November 20, 2010

Subjective Logic = Effective Logic?

Capture of Evidence for Summarization: An Application of Enhanced Subjective Logic

Authors(s): Sukanya Manna, B. Sumudu U. Mendis, Tom Gedeon Keywords: subjective logic, opinions, evidence, events, summarization, information extraction

Abstract:

In this paper, we present a method to generate an extractive summary from a single document using subjective logic. The idea behind our approach is to consider words and their co-occurrences between sentences in a document as evidence of their relatedness to the contextual meaning of the document. Our aim is to formulate a measure to find out ‘opinion’ about a proposition (which is a sentence in this case) using subjective logic in a closed environment (as in a document). Stronger opinion about a sentence represents its importance and are hence considered to summarize a document. Summaries generated by our method when evaluated with human generated summaries, show that they are more similar than baseline summaries.

The authors justify their use of “subjective” logic by saying:

pointed out that a given piece of text is interpreted by different person in a different fashion especially in the way how they understand and interpret the context. Thus we see that human understanding and reasoning is subjective in nature unlike propositional logic which deals with either truth or falsity of a statement. So, to deal with this kind of situation we used subjective logic to find out sentences which are significant in the context and can be used to summarize a document.

“Subjective” logic means we are more likely to reach the same result as a person reading the text.

Search results as used and evaluated by people.

That sounds like effective logic to me.

Questions:

  1. Read the Audun Jøsang’s article Artificial Reasoning with Subjective Logic.
  2. Summarize three (3) applications (besides the article above) of “subjective” logic. (3-5 pages, citations)
  3. How do you think “subjective” logic should be modeled in topic maps? (3-5 pages, citations optional)

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