do they wish to easily confirm that suspicion? Around those issues sensitive to consumers, are they outraged when they encounter news articles with a clear case of bias? If a consumer could automatically know how accurate or biased a news story is, would they look at that metric?

[0007] The relevant questions to be addressed on the media generators side of the media equation include: who are writer's that sways the facts? What is the relative bias and accuracy of publications, editors, local and national writers and bloggers that are relied upon to give up to the minute information? Can that information be checked for accuracy easily searchable way?

[0008] Generally, people who take the time to consume news in a media obsessed world can easily see the relative bias of any news story. What is needed however are tools and the means by which to make it easier for people, consumers of media, and generators of media, to check for accuracy in the news source they are consuming and/or presenting. SUMMARY OF THE INVENTION

[0009] In one exemplary embodiment, Spin Spotter™ can rate news for bias and accuracy, which in turn provides users an immediate benchmark for the degree to which they, the user as a consumer, are being spun or deceived. Spin Spotter™ gives users smart-tools to edit existing news stories, and to share the results with their friends. Further, the system and method extends to monitoring television news with live-time bias and accuracy tools. In one embodiment, when using the automated tools, if a user disagrees with the score generated by the automated bias meter, a user is able to adjust the automated ranking of the preferred embodiment. Further the software weights consumer input very highly in determining the spin of a particular piece of news.

[0010] In one embodiment, Spin Spotter™ is a system and method to determine the relative bias and accuracy of news and/or media. In one exemplary embodiment, used by consumers, the system and methods interacts with a user as they consume news, alerting them to possible bias, providing context and fact-checking. In another embodiment, for advertisers for example, the system and method provides in depth touch points to reach a consumer/user's emotional "hot buttons" and "life- style-pillars" drawn from how they interact with system. In yet another embodiment, for example for a user in the field of public Relations and/or in the Political Advertising Industry, the system is a searchable omnibus of the issue-biases and accuracy ratings. For Publishers (newspapers, blogs and broadcasters) the system can analyze the content and the information cross- referenced by issue, writer and/or talent.

[0011] In one embodiment the systems and methods can be launched on sites that are identified as influential political blogs (sites that don't make or break news, but critique those who do so). For example, a liberal blog like The Huffington Post can have a tool that allows a consumer/urser to document the bias of Fox News. Or as another example, MichelleMalkin.com, can adopt a tool to measure the bias of CNN.

[0012] In one embodiment, the system and method uses a finite set or parameters that include, but are not limited, to the most common forms of bias in news pieces, defined in style books, journalism schools and by a proprietary journalism advisory board. The board , for example can be comprised of journalism professors and writers from the hard right, the hard left and the middle of the political spectrum who approve the definition of bias detection, as well as the relative weighting for each occurrence.

[0013] In an exemplary embodiment, a Spin Spotter™ Political Spectrum Index Algorithm can use a combination of technologies and processes to attach to operatives in politics (Consumer/Users, Officials, Publications, Groups and Writers) a Political Spectrum Index Score. An operative's score can be heuristically obtained, an algorithmically compiled score which determines their placement along the political spectrum from left (commonly called Liberal) to right (Commonly called conservative); the score can be gained by first laying out defining issues and where along the political spectrum such issues lie; this is accomplished from starting with the most polarizing and long term disagreements between Right and Left (e.g. Abortion, Gun Control, Military Intervention) as measured by long term polling, political research, issues research and theological vs non-theological acceptance. Next, the Spin Spotter™ technique can place issues of a lessening degree of polarization into the more middle section of the Political Spectrum Index.

[0014] In another embodiment, a Spin Spotter™ Content Bias Meter looks for a finite set of parameters: the most common forms of bias in news pieces — defined in style books, journalism schools and by Spin Spotter's™ journalism advisory board, peopled by journalism professors and writers from the hard right, the hard left and the middle of the political spectrum who approve the definition of bias detection, as well as the relative weighting for each occurrence. This system first works with the Political Spectrum Index scores by scanning news for an over-reliance upon sources of one placement on the political spectrum as defined by the Political Spectrum Index Algorithm (Liberal Groups, Liberal Politicians or Conservative Group or Conservative Politician) as the first factor for Bias. From there, the Spin Spotter™ Content Bias Meter scans for rhetorical techniques in a news pieces which slant the message; which, for example, can defined by common journalism ethics, style book guides and on a list of attributes created by using the Spin Spotter™ Media Scanning software to scan an historical representation of news from large news aggregators to arrive at a benchmark norm for bias and for neutrality.

[0015] In one embodiment, a benchmark of bias is established. To establish a benchmark, the technology starts by scanning a percentage of the last five years of news from, but not limited to, Reuters, The Associated Press, USA Today, The Wall Street Journal, The Washington Post and a random selection of locally written news articles. The software can read for the presence or absence of terms and words within a predefined set of parameters which, together, make up the most common examples of bias- embedding techniques. For example, un-attributed adjectives, "'far-leff Democrat Hillary Clinton", "The Bloodiest Day In Iraq History." While those statements may well be true, unless they are scientifically proven (the Earth is round), it is not the prerogative of the reporter to state them.

[0016] In order to make the diagnosis easier, not all adjectives have an equal value in the news business. There are trigger words and phrases: "retaliatory strike", "Christian fundamentalist", these phrases include judgmental adjectives because they require some form of judgment. A judgment leads to a form of benchmark, for example what is the bar for fundamentalism vs. observant-religion and who really struck first in the Israeli vs. Arab conflicts? A piece of news should come from investigating the matter and should include evidence, such as: "The Catholic and American Lutheran Churches define 'Bob 's Church ' as fundamentalist."

[0017] Bias and accuracy issues are not confined to words; Reuters was recently proven to have bought, and used doctored photographs meant to make damage to Lebanon appear greater than was the case during a bombing by Israeli troops. The doctoring was discovered by analyzing pixel-washing in a series of photos.

[0018] In order to determine accuracy and bias, one embodiment of the system and method uses a series of sources. These sources include but are not limited to: stories from the left and right, public information. The number and type of user corrections and hard readable facts. For example, if a reporter chooses to write a story stating "Record High Gas Prices Dog Bush" in 2006, the system and method can compare the available public data on inflation adjusted gas prices to offer context, if not correction to that piece. In this actual case, context indicates that, in fact, gas prices were much higher in the 1970' s under President Nixon, so the record set 2006 has context and correction.

[0019] In one embodiment, the system and method can capture a massive share of advertising revenues by being used by users every time they read the news. The market for advertising in digital news in 2007 in the United States is $16 Billion. The system and method rides along with news; and can be available in tool bars, browser extensions, widgets, and mobile extensions.

[0020] In another embodiment the system and method can further contain a destination, where users store, edit, correct and report stories, and where they can search for news, centrists sources or the opposite view. The system and method tracks what people think about opinion, such that the information can be further parsed by topic. Further what people report as bias and what people do when they encounter bias can be tracked. The system and method has the knowledge to be able to charge a premium to political advertisers while offering brand advertiser the ability to align their message with the core beliefs of their audience. Cultural Anthropology and Media Sciences indicate that people read toward their bias and they read to back up what they already believe. In one application, the system and method, by tracking these patterns, can offer politicians, their PR Firms, and Buying Agencies access to information about an important segment in American politics, e.g. the swing-voter. In addition, the system and method can offers users the swing-voter by identified topic. For instance, in the most recent run up to the democratic candidacy, in the close race between Senator Hillary Clinton and Senator Obama the swing topic between the two appeared to be Senator Clinton's vote for the Iraq War and Senator Obama' s consistent opposition to it. In this example, the system and method can offer either politician ad space next to war related news pieces. Further, the system and method tracks a large percentage of its audience's local papers and, as such, can sell all of the above by geography. Political spending is increasingly year round, as national issues advertising grows. But the system and methods knowledge of its reader' s socio-political likes and dislikes yields something of importance to brand advertisers, and further the ability to sell with emotional appeal to core beliefs rather than pure demography or geography. The system and method can track not just the users, but also the journalists and bloggers the users read.

[0021] In another embodiment, the system and method includes the omnibus opinion, accuracy and reaction search tool for users at ad agencies, consultant and PR firms, and generally in the business of politics.

[0022] These and other examples of the invention will be described in further

detail below.

BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Preferred and alternative examples of the present invention are described

in detail below with reference to the following drawings:

[0024] FIGURE 1 is a schematic representation systems and methods of determination of a Spin Spotter™ Political Spectrum Index and population of Database;

[0025] FIGURE 2 one embodiment of the invention, an embodiment of a Spin

Spotter™ Database Housing the Political Spectrum Index of Officials (OPSI), Writers

(WPSI), Groups (GPSI), Publications (PPSI) and Users (UCPSI) Created by Communication Genomics Bias-Tracker;

[0026] FIGURE 3, as in FIGURE 2 above, an exemplary embodiment of the

Political Spectrum Index, wherein data related to identified defining issues populate the

Index; [0027] FIGURE 4 an exemplary embodiment of the Spin Spotter™ Database; Heuristics and Crowd- sour cing, showing sponsoring groups;

[0028] FIGURE 5 an embodiment of the Political Spectrum Index, showing the weighting of supportive publications from far left to far right;

[0029] FIGURE 6 an embodiment of the Political Spectrum Index, showing the weighting of writers from far left to far right;

[0030] FIGURE 7 an embodiment of the Spin Spotter™ Methodology, showing as a first step ,an algorithm built in consideration of OPSI;

[0031] FIGURE 8 shows the fourth step of the Spin Spotter™ Methodology and OPSI Algorithm Build;

[0032] FIGURE 9 an embodiment of the Spin Spotter™ Methodology, showing OPSI Algorithm Build Step Three

[0033] FIGURE 10 an embodiment of the Spin Spotter™ Methodology, showing OPSI Algorithm Build Step Four

[0034] FIGURE 11 information as the second variable in the PPSI;

[0035] FIGURE 12 the PPSI Algorithm build Step 3; represents the Writers Political Spectrum Index as the third variable;

[0036] FIGURE 13 : The Spin Spotter™ Bias Benchmark;

[0037] FIGURE 14: Group Political Index Spectrum Process;

[0038] FIGURE 15: Group Political Index Spectrum Process, Algorithm Build Step 1; [0039] FIGURE 16: Group Political Index Spectrum Process, Algorithm Build Step 1 Legal Filings by Cause;

[0040] FIGURE 17: Writers' Political Index Spectrum Process, Algorithm Build Step One;

[0041] FIGURE 18: Writers' Political Index Spectrum Process, Algorithm Build Step One;

[0042] FIGURE 19: User's Political Index Spectrum Process, Algorithm Build Step 1;

[0043] FIGURE 20: User's Political Index Spectrum Process, Algorithm Build Step 2;

[0044] FIGURE 21 : User's Political Index Spectrum Process, Algorithm Build Step 3;

[0045] FIGURE 22: In one embodiment, Spin Spotter™ begins its process by scanning an historical base of news items;

[0046] FIGURE 23 : One exemplary embodiment of the invention is an Alert- bar that tracks what you read for Bias and encourages participation;

[0047] FIGURE 24 One exemplary embodiment of the invention is a Website destination;

[0048] FIGURE 25 a schematic representation applying the Spin Spotter™ Political Spectrum Heuristics;

[0049] FIGURE 26 a schematic representation of how the Spin Spotter™ Cluster measures connected media for political bias by scanning interconnections; and [0050] FIGURE 27 a schematic representation of one exemplary embodiment of

Spin Spotter™ heuristics and star-cluster system.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENT

[0051] In one embodiment of the invention, Spin Spotter™ is comprised of four pieces of technology utilizing a combination of heuristics and crowd- sourcing techniques: a database, a tool bar, a search engine and a text and audio screener. It preferably includes the ability to use technology to find, measure, rate and disclose a plurality of forms of political bias within a news story.

[0052] As shown in FIGURE 1, a Spin Spotter™ system and method can be, but is not limited to: a Political Spectrum Index, an algorithm that determines the place at where any Group, Official, User, Writer or Publication sits along the left to right political spectrum. Second, a Spin Spotter™ Media Scanner can feed the Spin Spotter™ Political Spectrum Index database with a rating for the actual rhetorical and photographic bias in the news from news producing organizations resulting in the method of tracking the political bias of any publication and writer by news topic. Third, a Spin Spotter™ tool bar which uses the above to alert users that they may be seeing a biased pieces of news, offer them alternatives to that bias, allow them to edit the bias or to disagree that there exists bias and, ultimately, provides users with a Spin Spotter™ Bias Search function to search for news by bias.

[0053] Turning again to FIGURE 2, the Spin Spotter™ Political Spectrum Index Database can be first populated by rating the political spectrum indexes of Officials, Writers, Groups, Publications, and Users. The Database houses the Political Spectrum Index of Officials (OPSI), Writers (WPSI), Groups (GPSI), Publication (PPSI) and Users (UCPSI) crated by communication genomics bias-tracker. The Spin Spotter™ Political Spectrum Database can then be populated by scanning historical ranges of news media to determine a "benchmark bias norm" and to find neutral publications and writers. The Spin Spotter™ Political Spectrum Database can feed the Spin Spotter™ Toolbar and Spin Spotter™ Bias Search. Consumers can use the provided bias tool, which in turn feeds that information into the Spin Spotter™ Political Spectrum Index database.

[0054] In another embodiment, Spin Spotter™ is a Political Spectrum Index Score; an algorithm built upon the process described below. Once worked through the system, each participant in the political process has an individual score which enables Spin Spotter™ to automatically ascertain the political leanings -defined specifically, in one embodiment, as their Political Spectrum Index— of the various operatives in a given news story, e.g., writer, group, official, publication or even reader.

[0055] A Spin Spotter™ Master Data Base house the Political Spectrum Index Score of preferably all the participants in the human political activity, it is populated using a blend of heuristics and crowd sourcing including at least star-cluster maps, bunch- forming and affinity comparisons.

[0056] As exemplified in FIGURE 3, in one embodiment of the invention, a first defining issue can be used to establish the Political Spectrum Index, e.g., starting with an issue that can and/or tends to be polarizing -e.g., abortion, gun control, war, taxes, gay rights. Second, issues that tend to be less polarizing can be used to establish the outside edges of the Political Spectrum Index -e.g., public schools, the environment — toward the middle. Once these placements are established using publicly available data, an embodiment of Spin Spotter™ can use that as a baseline number for its algorithm building process and the resulting scores.

[0057] As exemplified in FIGURE 4, in one embodiment of the invention Spin Spotter™ can examine the political leanings of plurality of sponsorship groups. As one embodiment of the Political Spectrum Index, FIGURE 4 shows the weighting of sponsoring groups ranked from far left to far right. Spin Spotter™ examines the political leanings of each sponsoring group through a process described in more detail in FIGURES below.

[0058] FIGURE 5 is illustrative of another embodiment of the Political Spectrum Index, showing the weighting of supportive publications from far left to far right. In the array of publications, Spin Spotter™ examines the political leanings of each publication through a process described in more detail, below.

[0059] As exemplified in FIGURES 4, 5, and 6 in one embodiment of the invention Spin Spotter™ can rate a plurality of individual writers' sympathies to the defining issues using the methodology described through a process in more detail in FIGURES below.

[0060] In FIGURE 7 a Spin Spotter™ Methodology of the system is illustrated, where, as a first step an algorithm is built in consideration of Officials Political Spectrum Index (OPSI). The organizations most aligned with defining issues, and most opposed to one another, (NARAL as pro-abortion rights and The Right to Life Foundation as anti- abortion Rights) rank government office holders by their voting records. An embodiment of Spin Spotter™ uses these initial rankings, all publicly available, as a base number the algorithm which builds the OPSI (Official's Political Spectrum Index) — this applies across the range of issues.

[0061] The methodology utilized to determine the Spin Spotter™ Political Spectrum Index score is schematically depicted in FIGURE 7, using as an example Senator Hillary Rodham Clinton. In an exemplary embodiment, the Spin Spotter™ process builds an algorithm according to a combination of data and process. In this example, Senator Clinton's statistics, including, but not limited to, voting record, funding sources, rating by third parties, and composition of district, is processed to generate a Spin Spotter™ Policital Index Score.

[0062] Turning again to FIGURE 7, as a first step in an algorithm is built in consideration of Officials Public Political Spectrum Index (OPSI). Organizations most aligned with defining issues, and most opposed to one another, (e.g., NARAL as pro- abortion rights and The Right to Life Foundation as anti-abortion Rights) rank government office holders by their voting records. An embodiment of Spin Spotter™ uses these publicly available initial rankings, as a base number from which the algorithm builds the Official's Political Spectrum Index (OPSI). The OPSI this applies across the range of issues.

[0063] In FIGURE 8, a second step in this exemplary embodiment, the Spin Spotter™ methodology includes Senator Clinton's actual voting record and her binary position on defining issues as the second base number in the algorithm. This step is important because while the rankings of third-parties define a first variable of the OPSI Algorithm of step one, these groups are in and of themselves, biased. Adjusting the bias index according to this second variable, adjust for inherent bias in the first — especially in an election cycle, for example, when Officials tend to highlight areas of concern for themselves.

[0064] FIGURE 9 schematically demonstrates a third step of the Spin Spotter™ Methodology and OPSI Algorithm Build. Having already defined the PSI of groups in the political process as the second step, Spin Spotter™ preferably uses the publicly available data on campaign donations to Senator Clinton, and the aggregated PSI of the donors, to build the third number in the algorithm.

[0065] FIGURE 10 is a schematic Spin Spotter™ Methodology and the OPSI Algorithm Build. A last number variable added to the algorithm in this example represents those individuals who elected Senator Clinton, and their aggregated, community voting-record. The four variables are added to determine Senator Clinton's OPSI — in this simulated case, 21-L, meaning she is in the middle of the political left. The Spin Spotter™ methodology further provides ongoing analysis of Senator Clinton's OPSE, accommodating change over time and thus reflecting evolving data, e.g., as her positions evolve or she changes her mind on some issues. The system and method by building such an algorithm can provide a OPSE score for any official.

[0066] According to journalism ethics and style books, the easiest way to bias a story is to use only one side of the political aisle in quotes. As depicted in FIGURE 11, Spin Spotter's™ Bias Scanner scans publications to discover a reliance upon officials with a Political Spectrum Index (PSI) far to one side of the spectrum and/or absent another. This is the first variable used to build the PPSI algorithm. The Bias Scanner can track the PSFs of a plurality of candidates, issues and/or groups that a specified publication has endorsed, for example; the PPSI algorithm uses the information as the second number in the PPSI

[0067] FIGURE 10 depicts the third variable in the PPSI Algorithm build representing the Writers Political Spectrum Index.

[0068] As shown in FIGURE 11, the Bias Scanner also tracks the PSFs of the candidates, issues and groups that each publication has endorsed; the PPSI algorithm uses the information as the second number in the PPSI.

[0069] As shown in FIGURE 12, the Writers Political Spectrum Index represents a third variable in the PPSI Algorithm build.

[0070] FIGURE 13 depicts a Spin Spotter™ Bias Benchmark derived from screening rhetoric and photos in a news media sours, the PPSI algorithm uses the information as the fourth number in the PPSI.

[0071] FIGURE 14 schematically represents a Group Political Index Spectrum Process.

[0072] FIGURE 15 schematically represents the Group Political Index Spectrum Process, specifically an Algorithm Build Step 1.

[0073] FIGURE 16 schematically represents Group Political Index Spectrum Process, specifically Algorithm Build Step 1 Legal Filings by Cause.

[0074] FIGURE 17 schematically represents a Writers' Political Index Spectrum Process, specifically Algorithm Build Step 1.

[0075] FIGURE 18 schematically represents Writers' Political Index Spectrum Process, Algorithm Build Step One, The Spin Spotter™ Content Bias Engine is, again, the actual screening of the rhetoric of this writer, per-topic.

[0076] FIGURE 19 schematically represents a User's Political Index Spectrum Process, Algorithm Build Step 1. Having found the PSI of publications and writers, an embodiment of the UPSI uses the aggregated PSI of the user's publications of choice as the first part of the algorithm.

[0077] FIGURE 20 schematically represents the User's Political Index Spectrum Process, Algorithm Build Step 2. Similarly, the aggregate PSI of the user's preferred writers, as determined through observing the user's habits, is the second number.

[0078] FIGURE 21 schematically represents the User's Political Index Spectrum Process, Algorithm Build Step 3. The last number is determined using the Spin Spotter™ tool bar which draws its information from the Spin Spotter™ Content Bias Engine, scans for rhetorical bias in news pieces.

[0079] As represented in FIGURE 22 in one embodiment of the invention, the Spin Spotter™ process begins by scanning a historical base of news items and/or new sources, using the methodology described above, to scan for bias and, in so doing, to arrive at a "benchmark for bias 'norm'" and to determine the most neutral publications and writers by topic.

[0080] The Spin Spotter™ Content Bias Engine Scans News Articles, Blog Entries and Audio Video Presentations on political topics. The Spin Spotter™ scanner can track for the relative presence of bias inducing items as defined in the creation of the various Political Spectrum Indices and as compared against a large historical sample of news media sources. An article's Content Bias Engine scores news content as biased according to the degree to which an article clearly favors sources, spokespeople and officials from one side of the political spectrum as determined by giving their quotes much more space, or better placement, or using favorable adjectives to describe them ("moderate", "experienced") vs. operatives from the other end of the political spectrum index who are given less space, or placement later in the article or none at all and/or which the writer uses pejorative adjectives to describe them ("radical", "reactionary"). In addition to measuring favorable treatment of one side of the political spectrum, the Spin Spotter™ scanner can look for the presence of rhetorically biased writing as defined by journalism style books and ethics tombs. For example, an un-attributed adjective where the reporter clearly includes personal judgment, a headline that reads "Bush, hoping to thrill base, vetoes children's health" judges the President's motives and exaggerates what the president actually vetoes: a bill expanding under- written health care for children, not a bill that makes kids healthy.

[0081] In another embodiment, the Spin Spotter™ is a tool-bar which reads a specified article, listens to a specified piece of audio or the audio of a video clip, to spot bias and alert the consumer. When consumers use the tool, Spin Spotter™ tracks their bias preferences - which then contributes to the database. It is also a bias-based search engine which allows consumers and professionals to search for articles by bias rating, to report a biased article or to edit an article rated as biased. For professions in Public Relations, the search engine allows them to search to find, by their Political Spectrum Bias Rating, publication, writers all of them by topic. For example, a Public Relations professional, reacting to their Senator being accused by Minneapolis Police of soliciting sex in a bathroom, would be able search for the writers in Minneapolis most negative against the police and traditional sexual morality. The search engine can search The Spin Spotter™ Political Spectrum Index for relevant information.

[0082] In FIGURE 23 Spin Spotter is first a utility and second a destination. The utility is an Alert-bar that tracks what you read for Bias and encourages participation. SpinSpotter.com is the omnibus; search through UGV, all on Political Spin. It is also the home of Spin Spotter Pro.

[0083] FIGURE 24 depicts a Spin Spotter Website destination providing users and consumers with bias searching tools, including but not limited to, tertiary key word searching, but also provides for secondary ads to partner sites facilitating behavioral targeting.

[0084] FIGURE 25 schematically represents the Spin Spotter™ Political Spectrum Heuristics: The Spin Spotter™ Political Spectrum Index database is first populated by rating the political spectrum indexes of officials, writers, groups, publications, and users. The Spin Spotter™ Political Spectrum database is secondly populated by scanning a historical range of news to determine the "benchmark bias norm" and to find neutral publication and writers. The Spin Spotter™ Political Spectrum database feeds the Spin Spotter™ Toolbar and Spin Spotter™ Bias Search. The common usage patter for consumers with similar PSIs, the PPSI of similar web sites and the various interconnections of common sites and users crate a star cluster map based on political bias, a unique application with fees the Spin Spotter™ data base the data back into the system.

[0085] FIGURE 26: The Spin Spotter™ Cluster measures connected media for political bias by scanning interconnections, similar PSI scores, reliance on same sources and shared users-base

[0086] As schematically shown in FIGURE 27, The Spin Spotter™ political spectrum index database is first populated by rating the political spectrum indexes of officials, writers, groups, publications, and users. The Spin Spotter™ Political Spectrum database is secondly populated by scanning a historical range of news to determine the "benchmark bias norm" and to find neutral publication and writers. The Spin Spotter™ Political Spectrum database feeds the Spin Spotter™ Toolbar and Spin Spotter™ Bias Search. The common usage patter for consumers with similar PSIs, the PPSI of similar web sites and the various interconnects of common sites and users crate a star cluster map based on political bias, a unique application with fees the Spin Spotter™ data base the data back into the system.

[0087] While the preferred embodiment of the invention has been illustrated and described, as noted above, many changes can be made without departing from the spirit and scope of the invention. Accordingly, the scope of the invention is not limited by the disclosure of the preferred embodiment.

Claims

The embodiments of the invention in which an exclusive property or privilege is claimedare defined as follows:

1. A method implementable in at least one electronic device coupled to a network and a display device, comprising the steps of:

receiving, over the network, a data set related to at least one first topic reported by a news media source;

determining, based on the data set, a plurality of network sites hosting commentary of the at least one first topic;

determining, based on the data set, a bias index score of each site of the plurality;

determining, based on the data set, a plurality of authors providing the commentary hosted by the plurality of network sites;

determining, based on the data set, a bias index of each author of the plurality;

determining, based on the data set, a value characterizing the a bias score of each author on the first topic and the bias index score of the news source;

generating within a GUI a set of icons representing the plurality of sites and the plurality of authors, the icons being presented in multiple presentation formats based on the determined bias index scores and aggregate bias index values.

2. A search system comprising: a scanning system for searching for information relevant to a news media query associated with a first user in a plurality of users; a feedback system for receiving information found to be relevant to the query by other users; and and a content-based filter system for combining the information from the feedback system with the information from the scanning system and for filtering the combined information for relevance to at least one of the query and the first user.