CN112036157A - Foundation manager tone text analysis method and device - Google Patents
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Abstract
The application discloses a fund manager intonation text analysis method and device. The analysis method comprises the following steps: selecting a text object to be analyzed; performing word segmentation on an object to be analyzed of a text; screening the segmented text objects to be analyzed; forming various word cloud pictures; constructing and calculating tone enthusiasm and depolarity indexes of all fund managers; obtaining a fund manager tone overall index of the text object to be analyzed; and (4) drawing a trend graph changing along with time according to the time sequence of the overall tone index of the fund manager and the stock index. The device comprises: the system comprises a text selection module, a text word segmentation module, a screening module, a word cloud picture module, an index construction module, a calculation module, a total index module and a trend graph drawing module. The method and the system apply a text analysis technology to directly qualitatively and quantitatively analyze psychology and behaviors of the fund manager, are beneficial to analyzing and evaluating the tone enthusiasm and passivity of the fund manager by investors, and better make fund investment decisions.
Description
Technical Field
The application relates to the technical field of intonation and text analysis, in particular to a method and a device for analyzing intonation texts of fund managers.
Background
At present, analyzing the intonation text of a fund manager is particularly important in fund investment. The tone analysis and evaluation of the fund manager are beneficial to the investors to analyze the fund and the fund manager and carry out specific fund investment operation practice.
Aiming at the problem that an investor cannot evaluate, analyze and invest a fund product through unquantized data and information of a fund manager due to the fact that no fund manager tone text analysis method is established in the related technology, an effective solution is not provided at present.
Disclosure of Invention
The main purpose of the present application is to provide a fund manager intonation text analysis method and device, so as to solve the problem that the fund manager intonation text analysis method is not established in the related art, so that the investor cannot perform evaluation analysis and investment on fund products through unquantized data and information of the fund manager.
In order to achieve the above object, in a first aspect, the present application provides a fund manager intonation text analysis method, including:
in the sample period, aiming at a fund manager, selecting a text published by the fund manager as a text object to be analyzed;
performing word segmentation on a text object to be analyzed;
screening the segmented text objects to be analyzed;
carrying out word frequency statistics on the screened text to be analyzed to form various word cloud pictures;
aiming at a fund manager, constructing tone enthusiasm and depolarity indexes of the fund manager;
calculating tone enthusiasm and depolarizing indexes of all fund managers in a sample period;
summing the tone enthusiasm and depolarizing indexes of all fund managers in the sample period to obtain a total tone index of the fund managers of the text object to be analyzed;
and (3) drawing a trend graph changing along with time according to the time sequence of the fund manager tone overall index and the stock index of the text object to be analyzed in the sample period.
The text object to be analyzed is subjected to word segmentation by using a Python software Jieba module, and the word segmentation result at least comprises the following steps: verbs, adjectives, adverbs, nouns, quantitative words, punctuation, letters, conjunctions, pronouns.
The screening of the text object to be analyzed after word segmentation comprises the following steps:
according to the word segmentation results of all texts, the redundant words without information content are filtered, and the method comprises the following steps: punctuation marks, person name pronouns and connecting words;
according to the part of speech filtering, remove the irrelevant part of speech of this language intonation analysis, including: removing parts of speech marked with English, numbers, punctuation marks, names of people, place names, direction words, quantifier words and time words;
selecting out the parts of speech as adjectives, nouns and verbs.
The various word cloud pictures include: an adjective word cloud picture, a noun word cloud picture and a verb word cloud picture. The higher the frequency, the larger the words in the word cloud.
The construction of the tone enthusiasm and passivity indexes of the fund manager comprises the following steps:
constructing a vocabulary dictionary representing the positive and negative of the fund manager;
and constructing a fund manager tone enthusiasm and passivity index according to the vocabulary dictionary, wherein the formula is as follows:
wherein, Posi,tVocabulary count, Neg, representing the positive tone of the ith fund manager during the t sample periodi,tIndicates a negative intonation vocabulary count, Tone, for the ith fund manager during the t sample periodi,tRepresenting the net positive tone of the ith fund manager during the t sample period.
The construction of the vocabulary dictionary representing the active and passive of the fund manager comprises the following steps:
the words representing the active and passive of the fund manager are selected to construct a dictionary, and the words selected in the constructed letters are the words that appear in at least 1% of the textual objects to be analyzed. The dictionary comprises a plurality of active words and a plurality of passive words.
The value range of the tone positivity and negativity indexes of the fund manager is between [ -1,1 ].
The abscissa of the trend graph is time, and the ordinate is the total index of the fund manager tone and the stock index.
In a second aspect, the present application further provides a fund manager intonation text analysis apparatus, which is implemented by the fund manager intonation text analysis method, and includes: the system comprises a text selection module, a text word segmentation module, a screening module, a word cloud picture module, an index construction module, a calculation module, a total index module and a trend picture drawing module;
the text selection module, the text word segmentation module, the screening module, the word cloud picture module, the index construction module, the calculation module, the overall index module and the trend picture drawing module are sequentially connected;
the text selection module: the system is used for selecting the text published by a fund manager as a text object to be analyzed aiming at the fund manager in a sample period;
the text word segmentation module is used for segmenting words of the text object to be analyzed;
the screening module is used for screening the text objects to be analyzed after word segmentation;
the word cloud picture module is used for carrying out word frequency statistics on the screened texts to form various word cloud pictures;
the index construction module is used for constructing the language tone enthusiasm and passivity indexes of a fund manager aiming at the fund manager;
the calculation module is used for calculating tone enthusiasm and depolarizing indexes of all fund managers in a sample period;
the overall index module is used for summing and averaging the tone enthusiasm and the depolarizing indexes of all fund managers in the sample period to obtain a fund manager tone overall index of the text object to be analyzed, namely the fund manager tone enthusiasm index;
and the trend graph drawing module is used for drawing a trend graph changing along with time according to the time sequence of the fund manager tone overall index and the stock index of the text object to be analyzed in the sample period.
The beneficial technical effects are as follows:
the method and the system have the advantages that the psychology and the behavior of the fund manager are directly qualitatively and quantitatively analyzed through the normalized text information regularly disclosed by the fund product by using the text analysis technology, so that an investor can analyze and evaluate the tone enthusiasm and the passivity of the fund manager, and fund investment decision can be better carried out.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, serve to provide a further understanding of the application and to enable other features, objects, and advantages of the application to be more apparent. The drawings and their description illustrate the embodiments of the invention and do not limit it. In the drawings:
FIG. 1 is a flow chart of a fund manager intonation text analysis method according to an embodiment of the present application;
FIG. 2 is a trend chart of a fund manager intonation text analysis method according to an embodiment of the present application;
FIG. 3 is a cloud diagram of verb words provided in accordance with an embodiment of the present application;
FIG. 4 is an adjective cloud provided in accordance with an embodiment of the present application;
fig. 5 is a connection diagram of a fund manager intonation text analysis device according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the application described herein may be used. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In this application, the terms "upper", "lower", "left", "right", "front", "rear", "top", "bottom", "inner", "outer", "middle", "vertical", "horizontal", "lateral", "longitudinal", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings. These terms are used primarily to better describe the present application and its embodiments, and are not used to limit the indicated devices, elements or components to a particular orientation or to be constructed and operated in a particular orientation.
Moreover, some of the above terms may be used to indicate other meanings besides the orientation or positional relationship, for example, the term "on" may also be used to indicate some kind of attachment or connection relationship in some cases. The specific meaning of these terms in this application will be understood by those of ordinary skill in the art as appropriate.
In addition, the term "plurality" shall mean two as well as more than two.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
In a first aspect, the present application provides a fund manager intonation text analysis method, as shown in fig. 1, including the steps of:
step S1: in the sample period, aiming at a fund manager, selecting a text published by the fund manager as a text object to be analyzed; the embodiment selects the contents of 'brief prospects of managers for macroscopic economy, stock market and industry trend' in semiannual newspaper and annual newspaper of fund disclosure specification as the basis of text analysis. The sample period may be one year or half a year.
Step S2: performing word segmentation on a text object to be analyzed;
step S3: screening the segmented text objects to be analyzed;
step S4: carrying out word frequency statistics on the screened text to be analyzed to form various word cloud pictures;
step S5: aiming at a fund manager, constructing tone enthusiasm and depolarity indexes of the fund manager;
step S6: calculating tone enthusiasm and depolarizing indexes of all fund managers in a sample period;
step S7: summing and averaging the Tone enthusiasm and the depolarizing indexes of all Fund managers in the sample period to obtain a Fund Manager Tone overall Index of the text object to be analyzed, namely a Fund Manager Tone enthusiasm Index (FMTI);
step S8: and (3) drawing a trend graph changing along with time according to the time sequence of the fund manager tone general index and the stock index of the text object to be analyzed in the sample period, wherein the abscissa represents time, the left ordinate represents the tone index, and the right ordinate represents the percentage of the profitability of the stock.
The text object to be analyzed is subjected to word segmentation by using a Python software Jieba module, and the word segmentation result at least comprises the following steps: verbs, adjectives, adverbs, nouns, quantitative words, punctuation, letters, conjunctions, pronouns.
The screening of the text object to be analyzed after word segmentation comprises the following steps:
according to the word segmentation results of all texts, the redundant words without information content are filtered, and the method comprises the following steps: punctuation marks, person name pronouns and connecting words;
according to the part of speech filtering, remove the irrelevant part of speech of this language intonation analysis, including: removing parts of speech marked with English, numbers, punctuation marks, names of people, place names, direction words, quantifier words and time words;
selecting out the parts of speech as adjectives, nouns, verbs and phrases.
The various word cloud pictures include: an adjective word cloud picture, a noun word cloud picture and a verb word cloud picture. The higher the frequency, the larger the words in the word cloud. The dictionary vocabulary constructed in the embodiment has the word cloud images of the vocabulary with the appearance frequency of the top 150, as shown in fig. 3 and 4.
The construction of the tone enthusiasm and passivity indexes of the fund manager comprises the following steps:
constructing a vocabulary dictionary representing the positive and negative of the fund manager;
and constructing a fund manager tone enthusiasm and passivity index according to the vocabulary dictionary, wherein the formula is as follows:
wherein, Posi,tVocabulary count, Neg, representing the positive tone of the ith fund manager during the t sample periodi,tIndicates a negative intonation vocabulary count, Tone, for the ith fund manager during the t sample periodi,tRepresenting the net positive tone of the ith fund manager during the t sample period. The larger the value, the more aggressive the fund manager's judgment of the future situation. The intonation positivity and negativity indexes of the fund manager range from [ -1,1]In the meantime.
The construction of the vocabulary dictionary representing the active and passive of the fund manager comprises the following steps:
and selecting words representing the positive and negative of the fund manager to construct a dictionary, wherein the words selected in the constructed letters are at least the words appearing in 1% of text samples, so that the problem of word use rarely caused by the personal style of the fund manager is avoided. Firstly, the words are manually read, representative positive and negative words are selected according to Chinese language habits, and a dictionary is formed, wherein the dictionary comprises a plurality of positive words (more than 100) and a plurality of negative words (more than 100).
In a second aspect, the present application further provides a fund manager intonation text analysis apparatus, which is implemented by the fund manager intonation text analysis method, and includes: the system comprises a text selection module, a text word segmentation module, a screening module, a word cloud picture module, an index construction module, a calculation module, a total index module and a trend picture drawing module;
the text selection module, the text word segmentation module, the screening module, the word cloud picture module, the index construction module, the calculation module, the overall index module and the trend picture drawing module are sequentially connected, as shown in FIG. 5;
the text selection module: the system is used for selecting the text published by a fund manager as a text object to be analyzed aiming at the fund manager in a sample period;
the text word segmentation module is used for segmenting words of the text object to be analyzed;
the screening module is used for screening the text objects to be analyzed after word segmentation;
the word cloud picture module is used for carrying out word frequency statistics on the screened texts to form various word cloud pictures;
the index construction module is used for constructing the language tone enthusiasm and passivity indexes of a fund manager aiming at the fund manager;
the calculation module is used for calculating tone enthusiasm and depolarizing indexes of all fund managers in a sample period;
the overall index module is used for summing and averaging the tone enthusiasm and the depolarizing indexes of all fund managers in the sample period to obtain a fund manager tone overall index of the text object to be analyzed, namely the fund manager tone enthusiasm index;
and the trend graph drawing module is used for drawing a trend graph changing along with time according to the time sequence of the fund manager tone overall index and the stock index of the text object to be analyzed in the sample period.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A fund manager intonation text analysis method is characterized by comprising the following steps:
in the sample period, aiming at a fund manager, selecting a text published by the fund manager as a text object to be analyzed;
performing word segmentation on a text object to be analyzed;
screening the segmented text objects to be analyzed;
carrying out word frequency statistics on the screened text to be analyzed to form various word cloud pictures;
aiming at a fund manager, constructing tone enthusiasm and depolarity indexes of the fund manager;
calculating tone enthusiasm and depolarizing indexes of all fund managers in a sample period;
summing the tone enthusiasm and depolarizing indexes of all fund managers in the sample period to obtain a total tone index of the fund managers of the text object to be analyzed;
and (3) drawing a trend graph changing along with time according to the time sequence of the fund manager tone overall index and the stock index of the text object to be analyzed in the sample period.
2. The fund manager intonation text analysis method according to claim 1,
the text object to be analyzed is subjected to word segmentation, and the word segmentation result at least comprises the following steps: verbs, adjectives, adverbs, nouns, quantitative words, punctuation, letters, conjunctions, pronouns.
3. The fund manager intonation text analysis method according to claim 1,
the screening of the text object to be analyzed after word segmentation comprises the following steps:
according to the word segmentation results of all texts, the redundant words without information content are filtered, and the method comprises the following steps: punctuation marks, person name pronouns and connecting words;
according to the part of speech filtering, remove the irrelevant part of speech of this language intonation analysis, including: removing parts of speech marked with English, numbers, punctuation marks, names of people, place names, orientation words, quantifier words and time words;
selecting out the parts of speech as adjectives, nouns and verbs.
4. The fund manager intonation text analysis method according to claim 1,
the various word cloud pictures include: an adjective word cloud picture, a noun word cloud picture and a verb word cloud picture.
5. The fund manager intonation text analysis method according to claim 1,
the construction of the tone enthusiasm and passivity indexes of the fund manager comprises the following steps:
constructing a vocabulary dictionary representing the positive and negative of the fund manager;
and constructing a fund manager tone enthusiasm and passivity index according to the vocabulary dictionary, wherein the formula is as follows:
wherein, Posi,tVocabulary count, Neg, representing the positive tone of the ith fund manager during the t sample periodi,tIndicates a negative intonation vocabulary count, Tone, for the ith fund manager during the t sample periodi,tRepresenting the net positive tone of the ith fund manager during the t sample period.
6. The fund manager intonation text analysis method according to claim 5,
the construction of the vocabulary dictionary representing the active and passive of the fund manager comprises the following steps:
the words representing the active and passive of the fund manager are selected to construct a dictionary, and the words selected in the constructed letters are the words that appear in at least 1% of the textual objects to be analyzed.
7. The method as claimed in claim 6, wherein said dictionary comprises a plurality of active words and a plurality of passive words.
8. The fund manager intonation text analysis method according to claim 5, wherein the fund manager intonation enthusiasm and passivity index range is between [ -1,1 ].
9. The method as claimed in claim 1, wherein the abscissa of the trend graph is time, and the ordinate is the total index of the fund manager tone and the stock index.
10. A fund manager intonation text analysis apparatus, implemented by the fund manager intonation text analysis method according to any one of claims 1 to 9, comprising: the system comprises a text selection module, a text word segmentation module, a screening module, a word cloud picture module, an index construction module, a calculation module, a total index module and a trend picture drawing module;
the text selection module, the text word segmentation module, the screening module, the word cloud picture module, the index construction module, the calculation module, the overall index module and the trend picture drawing module are sequentially connected;
the text selection module: the system is used for selecting the text published by a fund manager as a text object to be analyzed aiming at the fund manager in a sample period;
the text word segmentation module is used for segmenting words of the text object to be analyzed;
the screening module is used for screening the text objects to be analyzed after word segmentation;
the word cloud picture module is used for carrying out word frequency statistics on the screened text to be analyzed to form various word cloud pictures;
the index construction module is used for constructing the language tone enthusiasm and passivity indexes of a fund manager aiming at the fund manager;
the calculation module is used for calculating tone enthusiasm and depolarizing indexes of all fund managers in a sample period;
the overall index module is used for summing and averaging the tone enthusiasm and the depolarizing indexes of all fund managers in the sample period to obtain a fund manager tone overall index of the text object to be analyzed;
and the trend graph drawing module is used for drawing a trend graph changing along with time according to the time sequence of the fund manager tone overall index and the stock index of the text object to be analyzed in the sample period.
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