Talk:Social search/Archive 1

Archive 1

social searching

This is an update to social searching which needed work achieve a better encyclopedia style and was marked as requiring cleanup to meet Wikipedia's quality standards. I also moved it from social searching to social search to be more parallel with similar terms such as search rather than 'searching' and search spam rather than 'search spamming'.

I tried to achieve a more NPV. To the previous editors, I hope you don't mind such a big change, but it really needed work. I tried to preserve most of the existing content but wrapped it in more defensible material and some references. Still needed: more history, more references, move the company links out of the article and into articles for the companies themselves if they have them. Mtanne 09:23, 28 December 2006 (UTC)

Looks great so far. Glad to see that it remains an article. It did need a lot of work, thanks for your contributions! (Toritaiyo 17:01, 12 March 2007 (UTC))

Lerato phakoe SAMUEL Lerato Phakoe SAMUEL (talk) 21:53, 19 January 2020 (UTC)

Relevance feedback

I guess this is the non-technical definition relevance feedback, a technology that has been under research for decades before this commercially oriented and naive article says. I think it needs to be harmonized with the article on relevance feedback. Furthermore, the commercial references should be removed or at least moved to list of search engines. Josh Froelich 19:04, 17 January 2007 (UTC)

Agree that this should be harmonized with relevance feedback, however a distinction should be maintained between human feedback, where the human could be editors, testers, etc. versus input from a large network of end users, which is a relatively newer phenomenon. e.g. large numbers of editors edited conventional encyclopedias, but wikipedia was still a new phenomenon worth describing since the editorial process is owned by the audience. Mtanne 11:00, 7 June 2007 (UTC)

Accuracy

Social search is not emerging. Some of the claims in the current version imply that certain listed companies dominate a marketspace. This is market-speak and simply untrue. This article needs to be written with the proper context, that of relevance feedback, a concept in use for over a decade, contrary to the uncited claims in this current revision. Josh Froelich 01:01, 30 January 2007 (UTC)

I rephrased the intro sentence to indicate that those companies did not invent nor dominate social search, but that they were among the earliest companies where the new term was used to describe what they are doing. I removed the accuracy template, because what it states now is factual correct. Who came up with the term or definition is still unclear and requires research and valid references to proof it. --roy<sac> ^Talk! .oOo. 00:41, 1 December 2007 (UTC)

Accuracy

"The term social search began to emerge between 2004 and 2005" Is there a source for this? Would be interesting to know.

Tony M 10 April 2009 —Preceding unsigned comment added by 220.245.46.203 (talk) 22:06, 9 April 2009 (UTC)

Update to this article

Hi!

The term social search has been co-opted by many in the tech industry to refer to the act of using social network contacts (twitter, FB) to help produce search results. Bing has just rolled out some features directly related to what I am saying. Does anyone disagree with taking the article in that direction? A. Ward (talk) 02:40, 1 June 2011 (UTC)

Suggestions for improving the article

From my point of view, this article needs to be improved in many aspects.
1. It’s long way from meeting the first criteria of six good article criteria, well written, even in its first paragraph. The one sentence definition is short but not clear at all. It just uses another term, social graph, to explain the current term. Besides, the “concern” isn’t well organized either. There should be an overall summary of the concern instead of only talking about Google in the first place.
2. The article also missed the second criteria, verifiable. If you click on the first reference link, you would find that the original article said there wasn’t even a good definition of “social search”. However, the previous author just gave an unclear definition for it based on the article just mentioned. Besides, the reference article doesn’t even mention the term “social graph”.
3. There is no illustration in this article. Illustrations like interface for social search and graph will better explain the article.
I believe if we could solve these problems, the quality of the article would be much better.
SapphireH (talk) 06:15, 28 October 2015 (UTC)

Lerato phakoe SAMUEL Lerato Phakoe SAMUEL (talk) 21:57, 19 January 2020 (UTC)

Some suggestions

Firstly, I agree with SapphireH that there are some problems in first paragraph. In current version, it is hard for readers to understand Social Search using some other unfamiliar terms. We should assume that readers have little knowledge in relative areas. So we have to find out some other ways to explain the term "Social Search" in general.

Secondly, I think that "Social Discovery" seems abrupt to appear here because there is no explanation for relationship between term "Social Search" and "Social Discovery". We should add more information here to let user know why we want to explain "Social Discovery" here.

Zenithda (talk) 00:59, 31 October 2015 (UTC)

Another some suggestions:

Obviously, this article does not explain this concept very concisely for beginners and also it is not much valuable for people who want to know this field further.

1. I agree with SapphireH. The definition of social search should be improved. After a definition, we can add some example or phases in social search and it will help beginners on this field to understand.

2. As for concern part, only Google for example is not actually enough. We can list what some social search really consider about and it is for reader to understand what this search is doing and relationship to our daily life.

3. Adding figures is necessary to be intuitive to understand. We can make some activity flows to explain the processing phases for readers.

Besides, I think the “social discovery” was merged into Social search. So, we can only focus on the social search. (for Zenithda) I am glad to take care of the part to explain the what Social search concerns about.

Jpotato0o (talk) 21:47, 1 November 2015 (UTC)

Some summaries from my end

As what we discussed above, there are several things in this article we need to fix.
1. Give a concise and understandable definition for social search instead of the current one.
2. Merge "social discovery" into other part of the article or add in more connections among other parts. It seems to be so abrupt here.
3. More graphs and figures for readers to better understand social search.
You guys are welcomed to comment my second point mentioned from my last post.
If you have any other suggestions or advices please feel free to leave a message in my talk page. Thank you!
SapphireH (talk) 19:03, 1 November 2015 (UTC)

Something to make sure about using activity or figure

For the third point of JPotato, I think we need remember that we should use activities and figures in some reference materials to explain term instead of creating them by ourselves because of second criteria of Wikipedia which says that "Verifiable with no original research".

Zenithda (talk) 16:19, 2 November 2015 (UTC)

Reply for figures

Of course, we can do that to find some figures built already and it is a better and more authoritative way. What we need do is to make this article richer and people could get information they want.

Jpotato0o (talk) 19:49, 3 November 2015 (UTC)

Suggestions_INFSCI 2430 Social Computing

I agree with the above discussions among SapphireH, Zenithda and Jpotato0o. They have proposed ideas on how to improve the definition of Social Search and the sections of Concerns, Social discovery.

I think the content of the Section Developments is not enough. Research developments from other research groups, besides Google, should be included.

Decision of changes_INFSCI 2430 Social Computing

We are students of INFSCI 2430 Social Computing: SapphireH, Zenithda, Jpotato0o and Markjz86.

Based on our discussion, we will improve this document from the following points.

1. SapphireH: Give a concise and understandable definition for social search instead of the current one.

2. Zenithda: Merge "social discovery" into other part of the article or add in more connections among other parts. It seems to be so abrupt here.

3. Jpotato0o: More graphs and figures for readers to better understand social search.

4. Markjz86: The content of the Section Developments is not enough. Developments from other research groups, besides Google, should be included.

The improvement of definition about social search

Social search or a social search engine is an enhanced version of web search that combines traditional algorithm.The idea behind social search is that instead of a machine deciding which pages should be returned for a specific query based upon an impersonal algorithm, results that are based on the human network of the searcher might be more relevant to that specific user's needs.

Social search may not be demonstrably better than algorithm-driven search. In the algorithmic ranking model that search engines used in the past, relevance of a site is determined after analyzing the text and content on the page and link structure of the document. In contrast, search results with social search highlight content that was created or touched by other users who are in the Social Graph of the person conducting a search. It is a personalized search technology with online community filtering to produce highly personalized results. Social search takes many forms, ranging from simple shared bookmarks or tagging of content with descriptive labels to more sophisticated approaches that combine human intelligence with computer algorithms. Depending on the feature-set of a particular search engine, these results may then be saved and added to community search results, further improving the relevance of results for future searches of that keyword. The principle behind social search is that instead of computer algorithms deciding the results for specific queries, human network oriented results would be more meaningful and relevant for the user.

Benefits of social search:

• The retrieved results would be more relevant to the user and the needs because the results are culled from the content streams of human beings in your social groups.
• It can help in building a trusted network because social search provides a way to leverage a network of trusted people, relying more upon their own impression about a particular result being good or bad.
• Since the results are products of human involvement, it can be more helpful and relevant and would also help in bettering computer algorithms to suit different human networks.
• Negligible spamming occurs through social search, as it is more based on personal feedback.
• Social search also provides results which are current and up to data with even recent changes because there is a constant feedback loop involved.

Negatives of social search:

• Users directly add results to a social engine. Therefore, without proper control, users can be abused by the results with search spam.
• The long search terms are not very suited for social search due to low possibility to fill in all the searches with content users provide or fill in.

references

References

Jpotato0o (talk) 21:30, 15 November 2015 (UTC)

Improvement of the ‘Developments’ section (Draft without citations)

Confirmed to be in testing, a new Facebook app feature called 'Add a Link' lets users see popular articles they might want to include in their status updates and comments by entering a search query. The results appear to comprise articles that have been well-shared by other Facebook users, with the most recently published given priority over others. The option certainly makes it easier for users to add links without manually searching their News Feed or resorting to a Google query. This new app reduce users’ reliance on Google Search.

Twitter announced it is replacing its 'Discover' tab with 'Tailored Trends'. The new Tailored Trends feature, besides showing Twitter trends, will give a short description of each topic. Since trends tend to be abbreviations without context, a description will make it more clear what a trend is about. The new trends experience may also include how many Tweets have been sent and whether a topic is trending up or down.

Google may be falling behind in terms of social search, but in reality they see the potential and importance of this technology with Web 3.0 and web semantics. The importance of social media lies within how Semantic search works. Semantic search understands much more, including where you are, the time of day, your past history, and many other factors including social connections, and social signals. The first step in order to achieve this will be to teach algorithms to understand the relationship between things.

However this is not possible unless social media sites decide to work with search engines, which is difficult since everyone would like to be the main toll bridge to the internet. As we continue on, and more articles are referred by social media sites, the main concern becomes what good is a search engine without the data of users.

One development that seeks to redefine search is the combination of distributed search with social search. The goal is a basic search service whose operation is controlled and maintained by the community itself. This would largely work like Peer to Peer networks in which users provide the data they seems appropriate. Since the data used by search engines belongs to the user they should have absolute control over it. The infrastructure required for a search engine is already available in the from of thousands of idle desktops and extensive residential broadband access.

Despite of the advantages of distributed search, it shares several same security concerns as the traditionally centralized case. The security concerns can be classified into three categories: data privacy, data integrity and secure social search. Data privacy protection is defined as the way users can fully control their data and manage its accessibility. The solutions for data privacy include information substitution, attributed based encryption and identity based broadcast encryption. The data integrity is defined as the protection of data from unauthorized or improper modifications and deletions. The solutions for data integrity are digital signature, hash chaining and embedded signing key. The solutions for secure social search are blind signature, zero knowledge proof and resource handler.

Another issue related to both distributed and centralized search is how to more accurately understand user intent from observed multimedia data. The solutions are based on how to effectively and efficiently leverage social media and search engine. A potential method is to derive a user-image interest graph from social media, and then re-rank image search results by integrating social relevance from the user-image interest graph and visual relevance from general search engines.

Besides above engineering exploration, a more fundamental and potential method is to develop social search systems based on the understanding of related neural mechanisms. Search problems scale from individuals to societies, however, recent trends across disciplines indicate that the formal properties of these problems share similar structures and, often, similar solutions. Moreover, internal search (e.g., memory search) shows similar characteristics to external search (e.g., spatial foraging), including shared neural mechanisms consistent with a common evolutionary origin across species. For search scenarios, organisms must detect – and climb – noisy, long-range environmental (e.g., temperature, salinity, resource) gradients. Here, social interactions can provide substantial additional benefit by allowing individuals, simply through grouping, to average their imperfect estimates of temporal and spatial cues (the so-called ‘wisdom-of-crowds’ effect). Due to the investment necessary to obtain personal information, however, this again sets the scene for producers (searchers) to be exploited by others. — Preceding unsigned comment added by Markjz86 (talk • contribs) 14:01, 18 November 2015 (UTC)

One sentence definition for social search for the very beginning

Social search is a behavior of retrieving and searching on a social searching engine that mainly searches user-generated content such as news, videos and images related search queries on social media like Facebook, Twitter, Instagram and flickr.
A social search engine is an enhanced version of a search engine that combines traditional algorithm -driven technology with online community filtering to produce highly personalized results.

SapphireH (talk) 02:35, 24 November 2015 (UTC)

references

References

More detailed definition

A few social search engines depend only on online communities. Depending on the feature-set of a particular search engine, these results may then be saved and added to community search results, further improving the relevance of results for future searches of that keyword.

Social search engines are considered a part of Web 2.0 because they use the collective filtering of online communities to elevate particularly interesting or relevant content using tag ging. These descriptive tags add to the meta data embedded in Web pages, theoretically improving the results for particular keywords over time. A user will generally see suggested tags for a particular search term, indicating tags that have previously been added.

Potential drawbacks to social search lie in its open structure, as is the case with other tagged databases. As these are trust-based networks, unintentional or malicious misuse of tags in this context can lead to imprecise search results.

Several different versions of social engines have been launched, including Google Coop, Eurekster, Sproose, Rollyo, Anoox and Yahoo's MyWeb2.0.
SapphireH (talk) 02:51, 24 November 2015 (UTC)

references

References

Replacement for "Social discovery"

Social search engine

A social search engine is an enhanced version of a search engine that combines traditional algorithm -driven technology with online community filtering to produce highly personalized results. A few social search engines depend only on online communities. Depending on the feature-set of a particular search engine, these results may then be saved and added to community search results, further improving the relevance of results for future searches of that keyword.

Social search engines are considered a part of Web2.0 because they use the collective filtering of online communities to elevate particularly interesting or relevant content using tagging. These descriptive tags add to the meta data embedded in Web pages, theoretically improving the results for particular keywords over time. A user will generally see suggested tags for a particular search term, indicating tags that have previously been added.

Potential drawbacks to social search lie in its open structure, as is the case with other tagged databases. As these are trust-based networks, unintentional or malicious misuse of tags in this context can lead to imprecise search results.

Several different versions of social engines have been launched, including Google Coop, Eurekster, Sproose, Rollyo, Anoox and Yahoo's MyWeb2.0.

References

1. http://whatis.techtarget.com/definition/social-search-engine

Zenithda (talk) 18:29, 29 November 2015 (UTC)

graph about social search

File:Searchgraph 副本.jpg

Social Search

Jpotato0o (talk) 20:26, 29 November 2015 (UTC)

reference:

References

Social search graph

This is a vivid graph for social search I found on a blog.

File:Social search.png

SapphireH (talk) 05:26, 30 November 2015 (UTC)

References

Markjz86: Improvement of the ‘Developments’ section with citations

Developments

Confirmed to be in testing, a new Facebook app feature called 'Add a Link' lets users see popular articles they might want to include in their status updates and comments by entering a search query. The results appear to comprise articles that have been well-shared by other Facebook users, with the most recently published given priority over others. The option certainly makes it easier for users to add links without manually searching their News Feed or resorting to a Google query. This new app reduce users’ reliance on Google Search.[1]

Twitter announced it is replacing its 'Discover' tab with 'Tailored Trends'. The new Tailored Trends feature, besides showing Twitter trends, will give a short description of each topic. Since trends tend to be abbreviations without context, a description will make it more clear what a trend is about. The new trends experience may also include how many Tweets have been sent and whether a topic is trending up or down.[2][3]

Google may be falling behind in terms of social search, but in reality they see the potential and importance of this technology with Web 3.0 and web semantics. The importance of social media lies within how Semantic search works. Semantic search understands much more, including where you are, the time of day, your past history, and many other factors including social connections, and social signals. The first step in order to achieve this will be to teach algorithms to understand the relationship between things.[4]

However this is not possible unless social media sites decide to work with search engines, which is difficult since everyone would like to be the main toll bridge to the internet. As we continue on, and more articles are referred by social media sites, the main concern becomes what good is a search engine without the data of users.

One development that seeks to redefine search is the combination of distributed search with social search. The goal is a basic search service whose operation is controlled and maintained by the community itself. This would largely work like Peer to Peer networks in which users provide the data they seems appropriate. Since the data used by search engines belongs to the user they should have absolute control over it. The infrastructure required for a search engine is already available in the from of thousands of idle desktops and extensive residential broadband access.[5]

Despite of the advantages of distributed search, it shares several same security concerns as the traditionally centralized case. The security concerns can be classified into three categories: data privacy, data integrity and secure social search. Data privacy protection is defined as the way users can fully control their data and manage its accessibility. The solutions for data privacy include information substitution, attributed based encryption and identity based broadcast encryption. The data integrity is defined as the protection of data from unauthorized or improper modifications and deletions. The solutions for data integrity are digital signature, hash chaining and embedded signing key. The solutions for secure social search are blind signature, zero knowledge proof and resource handler.[6][7]

Another issue related to both distributed and centralized search is how to more accurately understand user intent from observed multimedia data. The solutions are based on how to effectively and efficiently leverage social media and search engine. A potential method is to derive a user-image interest graph from social media, and then re-rank image search results by integrating social relevance from the user-image interest graph and visual relevance from general search engines.[8][9]

Besides above engineering explorations, a more fundamental and potential method is to develop social search systems based on the understanding of related neural mechanisms. Search problems scale from individuals to societies, however, recent trends across disciplines indicate that the formal properties of these problems share similar structures and, often, similar solutions. Moreover, internal search (e.g., memory search) shows similar characteristics to external search (e.g., spatial foraging), including shared neural mechanisms consistent with a common evolutionary origin across species. For search scenarios, organisms must detect – and climb – noisy, long-range environmental (e.g., temperature, salinity, resource) gradients. Here, social interactions can provide substantial additional benefit by allowing individuals, simply through grouping, to average their imperfect estimates of temporal and spatial cues (the so-called ‘wisdom-of-crowds’ effect). Due to the investment necessary to obtain personal information, however, this again sets the scene for producers (searchers) to be exploited by others.[10]

[1] Constine, Josh (May 9, 2015). "Skip Googling With Facebook’s New “Add A Link” Mobile Status Search Engine". Techcrunch.

[2] Cselle, Gabor (April 8, 2015). "Updating trends on mobile". Twitter.

[3] Popper, Ben (April 2015). "Twitter is killing off its Discover tab".

[4] "Google Semantic Search". Social Media Today. 28 February 2014. Retrieved 1 December 2014.

[5] "Towards Distributed Social Search Engines". EPrints. Retrieved 1 December 2014.

[6] Boshrooyeh, Sanaz Taheri (June 2015). "Security and Privacy of Distributed Online Social Networks". Distributed Computing Systems Workshops (ICDCSW), 2015 IEEE 35th International Conference on. doi:10.1109/ICDCSW.2015.30.

[7] Unnikrishnan, Srija (2013). Advances in Computing, Communication, and Control. Springer. ISBN 978-3-642-36321-4.

[8] Liu, Shaowei (June 2013). "Social-oriented visual image search". Computer Vision and Image Understanding. doi:10.1016/j.cviu.2013.06.011.

[9] Cui, Peng (April 2014). "Social-Sensed Image Search". ACM Transactions on Information Systems. doi:10.1145/2590974.

[10] Hills, Thomas T. (January 2015). "Exploration versus exploitation in space, mind, and society". Trends in Cognitive Sciences. doi:10.1016/j.tics.2014.10.004.

Markjz86 to SapphireH & Jpotato0o: I will revise your updated content

Your updated content, i.e., definition of social search, clearly compare the pros and cons. I will only revise some minor errors and add references. The following are some examples:

(1) up to data -> up-to-date

(2) flickr -> Flickr

(3) algorithm -> algorithms

(4) social search -> Social search (in the figure caption)

— Preceding unsigned comment added by Markjz86 (talk • contribs) 13:24, 2 December 2015 (UTC)

Lead Section Improvement

The lead section needs some improvements starting with the definition of social search. The current definition is based on unreliable source, uses the almost exact wording of the reference, and the defines something else but not the social search concept. I found out that the definition describes a specific social media search engine, socialseeking.com. Also, the pros and cons of the social search are based on an unreliable source that only reflects a blogger opinion. Turkialenezi (talk) 21:34, 10 October 2016 (UTC)

Also, the subheadings "Benefits of social search" and "Negatives of social search" are mainly based on a personal opinion and reflect one person's point of view. The reference for those subheadings is a website to his blog about Social Search. Abdulazi2 (talk) 00:38, 24 October 2016 (UTC)

I agree with you. Generally, personal blogs content is not reliable source to be in a Wikipedia article. Turkialenezi (talk) 04:11, 24 October 2016 (UTC)

New Section: A Taxonomy of Social Search

Social search is a broad concept and the current version of the article does not clearly describe it. In order to understand the social search, it is important to understand how it's been used in different systems. Social search can be viewed in different categories that I believe it is crucial to add in this article.

(1) Collaboration: synchronous vs asynchronous.

(2) Collaboration: implicit vs explicit collaboration.

(3) Search target: finding people vs finding resources.

(4) Search results: sense-making vs content selection.

(5) Finding: search vs discovery. Turkialenezi (talk) 04:10, 24 October 2016 (UTC)

References

Social Search Engine Section Problems

This section has two main problems. First, the whole content of this section violates Wikipedia’s copyright policies and is a form of plagiarism. Second, the source is unreliable since it reflects an individual's opinion that posted in a website (whatis.com). This section should be rewritten based on reliable sources and according to Wikipedia's copyright policies. Turkialenezi (talk) 04:11, 24 October 2016 (UTC)

I have found two articles that talks about social search engine. We can use them as a reference in the process of rewriting this section Abdulazi2 (talk) 03:23, 28 October 2016 (UTC)

Social Discovery Section Suggestion

This section seems to be out-of-context. I suggest removing this section and add its content to the taxonomy of social search section once written, under the finding subsection. Turkialenezi (talk) 04:13, 24 October 2016 (UTC)

I concur, it does not seems to fit the topic, let alone has a section.Abdulazi2 (talk) 01:13, 27 October 2016 (UTC)

Combining History and Concerns sections into one section

The content of the history section and the Concerns section seems slimier. The history section contains information about the companies that have implemented social search such as google and Facebook with the dates. The "Concerns" section mostly contains the same information except no mention to the dates of when these companies invested in social search. So, it is probably a good idea to integrate these two sections into one section with a meaningful name such "Implementations of social search" Abdulazi2 (talk) 20:47, 24 October 2016 (UTC)

Improvements to the See Also section

Perhaps we can improve the See Also section by adding few relevant articles such as the Social Navigation once its lunched, and some examples of social search such as Facebook Graph Search and Google's PageRank Abdulazi2 (talk) 21:03, 24 October 2016 (UTC)

Articles Used

I used the following article to enrich and add content to the Researches and Implementations section

Barry Smyth, Peter Briggs, Maurice Coyle, and Michael O’Mahony.(2009) Google Shared. A Case-Study in Social Search.

As for the following article, it helped in redefining what a Social Search Engine is as well as providing a very good example of one. Damon Horowitz, Sepandar D. Kamvar (April 2010). The Anatomy of a Large-Scale Social Search Engine — Preceding unsigned comment added by Abdulazi2 (talk • contribs) 10:16, 9 December 2016 (UTC)

Pic

I have to get my friend on Facebook Lerato Phakoe SAMUEL (talk) 21:56, 19 January 2020 (UTC)