CN104408157A - Funnel type data gathering, analyzing and pushing system and method for online public opinion - Google Patents
Funnel type data gathering, analyzing and pushing system and method for online public opinion Download PDFInfo
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Abstract
The invention discloses a funnel type data gathering, analyzing and pushing system and method for online public opinion. The funnel type data gathering, analyzing and pushing system comprises an online public opinion gathering module, an online public opinion processing module and an online public opinion publishing module, and the modules comprise a directed precise gathering sub-module, a non-directive gathering sub-module, a hot spot and sensitive topic identifying sub-module, a topic tracking sub-module, an automatic abstracting sub-module, a comprehensive analysis sub-module, a public opinion pre-warning sub-module and a multi-dimensional public opinion information display sub-module. The funnel type data gathering, analyzing and pushing method for the online public opinion uses a special public opinion funnel algorithm and uses the lexicons of three types of keywords of related to me, public opinion and positive and negative aspects to analyze, judge and classify the gathered data and warn early to grasp the latent change rule. The funnel type data gathering, analyzing and pushing system and method for the online public opinion reduce the manual public opinion event polling burden, duly and precisely grasp the development trend of the public opinion event, form the latest, hottest and sensitive topics in the recent period on the Internet, and detect the public opinion message what the user is concerned about and give an early warning in the first time.
Description
Technical field
The present invention relates to network information processing technical field, particularly relate to the funneling data collection and analysis supplying system of a kind of network public-opinion and method.
Background technology
Internet develop rapidly in the world, the opening of network and virtual, determine network public-opinion and have following characteristics: be 1, direct: by BBS, News Comments and Blog Website, netizen can express an opinion immediately; Reach on lower feelings are direct, expresses public opinions is more unimpeded; 2, sudden: the formation of network public opinion is often very fast, the existence of a focus incident adds a kind of changeable in mood suggestion, just can become the safety fuse lighting a slice public opinion; 3, deviation: because spokesman's identity is hidden, and lack rule restriction and effectively supervision, nature network becomes the space of some netizen's venting emotions; Meet with setback in actual life, to social concern unilateral cognition etc., network all can be utilized to be led off.Therefore on network, more easily there is speech that is vulgar, grey.
Quantity of information on internet is very huge, and various informative, relies on the method for manual inspection public sentiment to be difficult to collection and the process of tackling online magnanimity information, and waste of manpower, material resources and time, thus incurs loss through delay guiding and the public sentiment disposal of public sentiment event.
Summary of the invention
The object of the invention is to overcome the deficiencies in the prior art, the funneling data collection and analysis supplying system of a kind of network public-opinion and method are provided, realize " very first time " " one-stop " and intellectual analysis carried out to the mass data that various network carrier (as news, forum, blog, microblogging, newpapers and periodicals, TV, search engine) gathers, steady, accurate, resolutely, soon internet is understood, read thin.In mass data fast, automatically push the public feelings information of user real concern accurately.
The object of the invention is to be achieved through the following technical solutions: the funneling data collection and analysis supplying system of a kind of network public-opinion, comprise network public-opinion acquisition module, network public-opinion processing module and network public-opinion release module, described network public-opinion acquisition module comprises directed precise acquisition submodule and non-directional gathers submodule, described directed precise acquisition submodule, for gathering the medium type website of news, forum, microblogging, blog, electronics report, Web TV public sentiment district occurred frequently, ensure that important information is not lost at very first time preferential collection; Described non-directional gathers submodule, and for gathering Baidu, GOOGLE, 360 main flow search engine data, carry out public sentiment data search and gather supplementary, it is comprehensive that guarantee information is collected;
Described network public-opinion processing module comprises focus and sensitive subjects recognin module, topic tracking submodule, autoabstract submodule and comprehensively analyzes submodule; Described focus and sensitive subjects recognin module are used for the hot issue, sensitive subjects and the just negative public feelings information that identify according to, public sentiment, the just negative three major types keyword dictionary relevant to me that arrange in system in section preset time; Described topic tracking submodule is newly published an article for analyzing, whether the topic of model is identical with existing theme; Described autoabstract submodule is used for all kinds of theme, and all kinds of tendency forms autoabstract; Described comprehensive analysis submodule, for according to the autoabstract formed, analyzes the degree of concern of certain theme between Different periods, prediction development trend; Carry out across the time, across spatial synthesis analysis to accident, know the overall picture that event occurs and the trend of predicted events development;
Described network public-opinion release module comprises public sentiment early warning submodule and various dimensions public feelings information shows submodule, described public sentiment early warning submodule is used for accident, the sensitive subjects Timeliness coverage relating to content safety reporting to the police, described various dimensions public feelings information shows submodule, for forming bulletin, report, chart to the analysis of public opinion result, be automatically pushed to user.
The funneling data collection and analysis method for pushing of network public-opinion, comprises the following steps:
(1) network public-opinion collection: directed precise acquisition is carried out to the medium type website of the news web page in local and overseas network, forum, microblogging, blog, electronics report, Web TV public sentiment district occurred frequently, non-directional collection is carried out to Baidu, GOOGLE, 360 main flow search engine data, to the information gathered back carry out duplicate removal, filter after stored in acquisition database;
(2) network public-opinion process, comprises following sub-step:
Whether S1, system, to the data analysis in acquisition database, are carried out analyzing according to dictionary relevant to me and are correlated with me, separate the information relevant with me and information for all I care;
S2, the system pair information relevant with me is analyzed, and whether belongs to public feelings information according to the analysis of public sentiment dictionary, separates public feelings information and non-public feelings information;
S3, system are analyzed public feelings information, the total number after cluster is carried out according to the website number of levels in this public feelings information source, the positive and negative keyword number of levels of this public sentiment, this public sentiment data similarity and the degree of correlation, three data are multiplied the long-pending focus value obtaining this public feelings information, identify hot information and non-hot information;
S4, system, according to just negative dictionary, adopt natural language Word Intelligent Segmentation technology, identify the positive Negative relation of information, separate negative report and non-negative report; Described just negative dictionary comprises Emotional Corpus and just negative public sentiment dictionary;
S5, system carry out topic tracking, and whether the topic analyzing the new article, model etc. issued is identical with existing theme; Autoabstract is formed to all kinds of theme; The information that collection is returned is carried out public sentiment Statistical Analysis of Key Words and is gone out the distribution situation of public sentiment keyword and carry out keyword clustering process by system, finally carry out generalized analysis to article title similarity again to judge to generate similarity associated data, thus realize a certain event topic trace analysis;
S6, system, according to the autoabstract formed, analyze the degree of concern of certain theme between Different periods, prediction development trend; The issuing time of every bar public feelings information is have recorded in detail in system public sentiment storehouse, website, the relevant information data such as carrier, these information is by the topic tracking analytical algorithm before us, detailed public sentiment route of transmission and the transmitting carrier of some event topic can be analyzed very easily, count frequency and probable value that public sentiment when section and what carrier occurs, finally system generates a public sentiment development trend figure intuitively;
S7, system is carried out across the time accident, across spatial synthesis analysis, the public sentiment data that every bar collection is returned is carried out cluster confluence analysis and is gone out the just negative rank of public sentiment by system, be distributed on each website time, be distributed on the frequency of each website and the focus correlative factor such as public sentiment route of transmission of the time formed according to issuing time and website, and according to the character of burst public sentiment event, the order of severity, rate of propagation, coverage, burst public sentiment event is divided into great especially public sentiment event by the key elements such as duration automatically, great public sentiment event, larger public sentiment event and general public sentiment event,
S8, system, according to the rank of burst public sentiment event, carry out public sentiment early warning;
(3) network public-opinion is issued: system, through graphic analyses trend, grasps potential Changing Pattern, the analysis of public opinion result is formed to the modes such as bulletin, report, chart, is automatically pushed to the public feelings information that user is concerned about.
Acquisition method described in step (1) adopts internet information acquisition, Text Mining Technology and global search technology Information Monitoring.
Public sentiment early warning described in step (2) comprises short message warning, mail early warning, plays window early warning.
The invention has the beneficial effects as follows: the network public-opinion monitoring and the directed tracking that realize user wait information requirement, form the analysis results such as bulletin, report, chart, user is helped to grasp public sentiment trend in time, accurate seizure early warning information, to having, the critical event of considerable influence finds fast, fast processing, and provide information foundation for user makes corresponding decision-making, greatly save man power and material's cost.
Accompanying drawing explanation
Fig. 1 is process flow diagram of the present invention.
Embodiment
Below in conjunction with accompanying drawing, technical scheme of the present invention is described in further detail, but protection scope of the present invention is not limited to the following stated.
As shown in Figure 1, the funneling data collection and analysis supplying system of a kind of network public-opinion, comprise network public-opinion acquisition module, network public-opinion processing module and network public-opinion release module, described network public-opinion acquisition module comprises directed precise acquisition submodule and non-directional gathers submodule, described directed precise acquisition submodule, for gathering the medium type website of news, forum, microblogging, blog, electronics report, Web TV public sentiment district occurred frequently, ensure that important information is not lost at very first time preferential collection; Described non-directional gathers submodule, and for gathering Baidu, GOOGLE, 360 main flow search engine data, carry out public sentiment data search and gather supplementary, it is comprehensive that guarantee information is collected;
Described network public-opinion processing module comprises focus and sensitive subjects recognin module, topic tracking submodule, autoabstract submodule and comprehensively analyzes submodule; Described focus and sensitive subjects recognin module are used for the hot issue, sensitive subjects and the just negative public feelings information that identify according to, public sentiment, the just negative three major types keyword dictionary relevant to me that arrange in system in section preset time; Described topic tracking submodule is newly published an article for analyzing, whether the topic of model is identical with existing theme; Described autoabstract submodule is used for all kinds of theme, and all kinds of tendency forms autoabstract; Described comprehensive analysis submodule, for according to the autoabstract formed, analyzes the degree of concern of certain theme between Different periods, prediction development trend; Carry out across the time, across spatial synthesis analysis to accident, know the overall picture that event occurs and the trend of predicted events development;
Described network public-opinion release module comprises public sentiment early warning submodule and various dimensions public feelings information shows submodule, described public sentiment early warning submodule is used for accident, the sensitive subjects Timeliness coverage relating to content safety reporting to the police, described various dimensions public feelings information shows submodule, for forming bulletin, report, chart to the analysis of public opinion result, be automatically pushed to user.
The funneling data collection and analysis method for pushing of network public-opinion, comprises the following steps:
(1) network public-opinion collection: directed precise acquisition is carried out to the medium type website of the news web page in local and overseas network, forum, microblogging, blog, electronics report, Web TV public sentiment district occurred frequently, non-directional collection is carried out to Baidu, GOOGLE, 360 main flow search engine data, to the information gathered back carry out duplicate removal, filter after stored in acquisition database;
(2) network public-opinion process, comprises following sub-step:
Whether S1, system, to the data analysis in acquisition database, are carried out analyzing according to dictionary relevant to me and are correlated with me, separate the information relevant with me and information for all I care;
S2, the system pair information relevant with me is analyzed, and whether belongs to public feelings information according to the analysis of public sentiment dictionary, separates public feelings information and non-public feelings information;
S3, system are analyzed public feelings information, the total number after cluster is carried out according to the website number of levels in this public feelings information source, the positive and negative keyword number of levels of this public sentiment, this public sentiment data similarity and the degree of correlation, three data are multiplied the long-pending focus value obtaining this public feelings information, identify hot information and non-hot information;
S4, system, according to just negative dictionary, adopt natural language Word Intelligent Segmentation technology, identify the positive Negative relation of information, separate negative report and non-negative report; Described just negative dictionary comprises Emotional Corpus and just negative public sentiment dictionary; Wherein about 90,000 sections of " emotion language material " storehouse, about 30,000 of just negative public sentiment dictionary, and rank evaluation and classification have been carried out to the negative keyword of every bar, emphasis monitors negative public sentiment, especially relate to corruption, relate to method, relate to discipline, be involved in drug traffic, relate to Huang, Concern Mafia, relate to probably etc. great public sentiment event, public sentiment language material and public sentiment dictionary every day all by manually and during machine self-teaching technology constantly expands;
S5, system carry out topic tracking, and whether the topic analyzing the new article, model etc. issued is identical with existing theme; Autoabstract is formed to all kinds of theme; The information that collection is returned is carried out public sentiment Statistical Analysis of Key Words and is gone out the distribution situation of public sentiment keyword and carry out keyword clustering process by system, finally carry out generalized analysis to article title similarity again to judge to generate similarity associated data, thus realize a certain event topic trace analysis;
S6, system, according to the autoabstract formed, analyze the degree of concern of certain theme between Different periods, prediction development trend; The issuing time of every bar public feelings information is have recorded in detail in system public sentiment storehouse, website, the relevant information data such as carrier, these information is by the topic tracking analytical algorithm before us, detailed public sentiment route of transmission and the transmitting carrier of some event topic can be analyzed very easily, count frequency and probable value that public sentiment when section and what carrier occurs, finally system generates a public sentiment development trend figure intuitively;
S7, system is carried out across the time accident, across spatial synthesis analysis, the public sentiment data that every bar collection is returned is carried out cluster confluence analysis and is gone out the just negative rank of public sentiment by system, be distributed on each website time, be distributed on the frequency of each website and the focus correlative factor such as public sentiment route of transmission of the time formed according to issuing time and website, and according to the character of burst public sentiment event, the order of severity, rate of propagation, coverage, burst public sentiment event is divided into great especially public sentiment event by the key elements such as duration automatically, great public sentiment event, larger public sentiment event and general public sentiment event,
S8, system, according to the rank of burst public sentiment event, carry out public sentiment early warning;
(3) network public-opinion is issued: system, through graphic analyses trend, grasps potential Changing Pattern, the analysis of public opinion result is formed to the modes such as bulletin, report, chart, is automatically pushed to the public feelings information that user is concerned about.
Acquisition method described in step (1) adopts internet information acquisition, Text Mining Technology and global search technology Information Monitoring.
Public sentiment early warning described in step (2) comprises short message warning, mail early warning, plays window early warning.
Claims (4)
1. the funneling data collection and analysis supplying system of network public-opinion, comprise network public-opinion acquisition module, network public-opinion processing module and network public-opinion release module, it is characterized in that: described network public-opinion acquisition module comprises directed precise acquisition submodule and non-directional gathers submodule, described directed precise acquisition submodule, for gathering the medium type website of news, forum, microblogging, blog, electronics report, Web TV public sentiment district occurred frequently, ensure that important information very first time preferential collection is not lost; Described non-directional gathers submodule, for gathering Baidu, GOOGLE, 360 current main-stream search engine data, carrying out public sentiment data search and gathering supplementary, ensure that the comprehensive of information;
Described network public-opinion processing module comprises focus and sensitive subjects recognin module, topic tracking submodule, autoabstract submodule and comprehensively analyzes submodule; Described focus and sensitive subjects recognin module are used for the hot issue, sensitive subjects and the just negative public feelings information that identify according to, public sentiment, the just negative three major types keyword dictionary relevant to me that arrange in system in section preset time; Described topic tracking submodule is newly published an article for analyzing, whether the topic of model is identical with existing theme; Described autoabstract submodule is used for all kinds of theme, and all kinds of tendency forms autoabstract; Described comprehensive analysis submodule, for according to the autoabstract formed, analyzes the degree of concern of certain theme between Different periods, prediction development trend; Carry out across the time, across spatial synthesis analysis to accident, know the overall picture that event occurs and the trend of predicted events development;
Described network public-opinion release module comprises public sentiment early warning submodule and various dimensions public feelings information shows submodule, described public sentiment early warning submodule is used for accident, the sensitive subjects Timeliness coverage relating to content safety reporting to the police, described various dimensions public feelings information shows submodule, for forming bulletin, report, chart to the analysis of public opinion result, be automatically pushed to user.
2. the funneling data collection and analysis method for pushing of network public-opinion, is characterized in that: comprise the following steps:
(1) network public-opinion collection: directed precise acquisition is carried out to the medium type website of the news web page in local and overseas network, forum, microblogging, blog, electronics report, Web TV public sentiment district occurred frequently, non-directional collection is carried out to Baidu, GOOGLE, 360 main flow search engine data, to the information gathered back carry out duplicate removal, filter after stored in acquisition database;
(2) network public-opinion process, comprises following sub-step:
Whether S1, system, to the data analysis in acquisition database, are carried out analyzing according to dictionary relevant to me and are correlated with me, separate the information relevant with me and information for all I care;
S2, the system pair information relevant with me is analyzed, and whether belongs to public feelings information according to the analysis of public sentiment dictionary, separates public feelings information and non-public feelings information;
S3, system are analyzed public feelings information, the total number after cluster is carried out according to the website number of levels in this public feelings information source, the positive and negative keyword number of levels of this public sentiment, this public sentiment data similarity and the degree of correlation, three data are multiplied the long-pending focus value obtaining this public feelings information, identify hot information and non-hot information;
S4, system, according to just negative dictionary, adopt natural language Word Intelligent Segmentation technology, identify the positive Negative relation of information, separate negative report and non-negative report; Described just negative dictionary comprises Emotional Corpus and just negative public sentiment dictionary;
S5, system carry out topic tracking, and whether the article of the new issue of analysis, the topic of model be identical with existing theme; Autoabstract is formed to all kinds of theme; The information that collection is returned is carried out public sentiment Statistical Analysis of Key Words and is gone out the distribution situation of public sentiment keyword and carry out keyword clustering process by system, carry out generalized analysis to article title similarity to judge to generate similarity associated data, realize a certain event topic trace analysis;
S6, system, according to the autoabstract formed, analyze the degree of concern of certain theme between Different periods, prediction development trend; The issuing time of every bar public feelings information is recorded in detail in system public sentiment storehouse, website and carrier information data, by topic tracking analytical algorithm, analyze detailed public sentiment route of transmission and the transmitting carrier of some event topic, count frequency and probable value that public sentiment when section and what carrier occurs, generate a public sentiment development trend figure intuitively;
S7, system is carried out across the time accident, across spatial synthesis analysis, the public sentiment data that every bar collection is returned is carried out cluster confluence analysis and is gone out the just negative rank of public sentiment by system, be distributed on each website time, be distributed on the frequency of each website and the time formed according to issuing time and these focus factors of public sentiment route of transmission of website, and according to the character of burst public sentiment event, the order of severity, rate of propagation, coverage, burst public sentiment event is divided into great especially public sentiment event by duration component automatically, great public sentiment event, larger public sentiment event and general public sentiment event,
S8, system, according to the rank of burst public sentiment event, carry out public sentiment early warning;
(3) network public-opinion is issued: system, through graphic analyses trend, grasps potential Changing Pattern, the analysis of public opinion result is formed to the modes such as bulletin, report, chart, is automatically pushed to the public feelings information that user is concerned about.
3. the funneling data collection and analysis method for pushing of network public-opinion according to claim 2, is characterized in that: the acquisition method described in step (1) adopts internet information acquisition, Text Mining Technology and global search technology Information Monitoring.
4. the funneling data collection and analysis method for pushing of network public-opinion according to claim 2, is characterized in that: the public sentiment early warning described in step (2) comprises short message warning, mail early warning, plays window early warning.
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