Most customers analyze sentiment trends through media monitoring dashboards (Figure 1) or reports. Larger customers can access our data in the form of rich documents through the Fairhair.ai data platform.
From the perspective of natural language processing technology, the task of sentiment analysis is to extract the entity of the review from the text of the review, as well as the emotional tendency expressed by the reviewer on the entity, and all the core technical issues of natural language. Therefore, sentiment analysis is considered a subtask of natural language processing.
Overview target sentiment analysis is to analyze the emotional tendency for people to entities and their attributes and the views expressed from the text
- In the field of public opinion, the trend of public opinion can be effectively grasped by analyzing the public's comments on social hot events.
- In terms of corporate public opinion, the use of sentiment analysis can quickly understand the society’s evaluation of the company, provide a basis for decision-making for the company’s strategic planning, and enhance the company’s competitiveness in the market.
- In the field of financial transactions, analyze traders' attitudes towards stocks and other financial derivatives, and provide auxiliary basis for market transactions.
Granularity selection
How to make the machine understand the real emotions is still a difficult problem that has not been overcome.
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Sentiment Analysis
Also known as tendency analysis, or opinion mining, it is the process of analyzing, processing, inducing and reasoning about subjective texts with emotional colors. With the ability of sentiment analysis, it can automatically judge the positive and negative sentiment tendency of the text with subjective description and give corresponding results.
Sentiment analysis is a field in natural language processing (NLP) that involves identifying and classifying subjective opinions from text [1]. Sentiment analysis ranges from detecting emotions (such as anger, happiness, fear) to sarcasm and intentions (such as complaints, feedback, opinions). Sentiment analysis in its simplest form assigns attributes (for example, positive, negative, neutral) to a piece of text.
Most of our customers analyze sentiment trends through media monitoring dashboards (Figure 1) or reports. Larger customers can access our data in the form of rich documents through the Fairhair.ai data platform.
The user can override the sentiment value assigned by the algorithm. The overridden sentiment attributes are indexed as different "versions" of the same document in Meltwater's Elasticsearch cluster, providing customers with a personalized view of their sentiment when building dashboards and reports (Figure 2)
Sentence-level and entity-level emotions in 16 languages.
The new model considers # tags, such as #love, emoticons and emoticons.
We have a feedback loop to continuously improve our emotional model.
Sentiment analysis helps to check whether customers are satisfied with the goods or services. Traditional public opinion surveys have long faded out of sight. Even those who want to support brands or political candidates are not always willing to spend time filling out questionnaires. However, people are willing to share their opinions on social networks. Searching for negative text and identifying major complaints can significantly help change concepts, improve products and advertisements, and reduce the level of dissatisfaction. In turn, clear positive reviews will increase ratings and demand.
Audio barrage yuy
Preferences
Who is the target user of this product? What are their needs? Can the product meet their needs? In addition, we must also consider the company's sustainable development requirements.
Good products" must meet both user goals and company goals
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Little red book product experience analysis: product planning and prospects!
2. Product Brief
2.1 Industry analysis
2.2 Product overview
2.3 Demand analysis
3. Product analysis
3.1 Product architecture
Function 4 product purchase
5 Product interaction
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The function of the voice barrage is to allow users to sing along instantly while watching the video
Compared with pure text, the voice barrage is also more personalized in the style of the audition. After all, everyone's timbre is unique. Jingming also designed a variety of animation skins for the voice barrage.
Voice barrage: more vivid, more personalized, more complex
Cold start phase
Of course, the intercommunication of emotions, empathy, viewpoint support, curiosity and satisfaction of new perspectives, analysis and auxiliary understanding of video content, and even combativeness between barrage and content... Every small point is a long discussion. It is certain that the barrage is up
A rough reason: fun and interesting. But the effect may be beyond imagination.
Sentiment analysis ranges from detecting emotions (such as anger, happiness, fear) to sarcasm and intentions (such as complaints, feedback, opinions). Sentiment analysis in its simplest form assigns attributes (for example, positive, negative, neutral) to a piece of text.
table of Contents
1. Product overview
Barrage sentiment analysis is an area of natural language processing (NLP) that involves identifying and classifying subjective opinions from text.
The user's sentiment analysis using barrage helps to check whether customers are satisfied with the goods or services. Traditional public opinion surveys have long faded out of sight. Even those who want to support brands or political candidates are not always willing to spend time filling out questionnaires. However, people are willing to share their opinions on social networks. Searching for negative text and identifying major complaints can significantly help change concepts, improve products and advertisements, and reduce the level of dissatisfaction. In turn, clear positive reviews will increase ratings and demand.
The product function is divided into three parts: the traditional bullet screen sentiment analysis module, the audio bullet screen sentiment analysis module, and the analysis module according to the sentiment value assigned by the user
2. Market analysis
2.1 Product background
From the perspective of the enterprise, this product is intended to assist products that support the main business. From business effect analysis and insights, multiple channels, multiple scenarios, multiple data application scenarios, and stimulate behavioral data value
From the perspective of outside the company, this product analyzes the emotional trend and obtains the corresponding results in the direction of the interoperability of emotions, empathy, viewpoint support, and new perspectives of curiosity and satisfaction related to the bullet screen and the content, thereby changing the content
2.2 Product market overview
Compared with the video, the barrage is real-time, and it is more impulsive emotion, which is more perceptual; almost all timely design interactive platforms have open barrage. As the Chinese version of utube's B station, it can be said to be barrage. Leaders, so that there is a topic about the barrage etiquette at station B. The popular barrage is just the beginning from the current situation. Later, it may be transformed from text, labels, symbols and other barrage forms into language. Image and other barrage, so we need a powerful product that is ahead of the current level of analyzing barrage emotions
2.3 Market demand for products
The barrage is generated during the video playback process. The dialogue atmosphere of the barrage is stronger, which can better connect users, or the atmosphere is more harmonious. The sentiment analysis technology is used to extract the emotional data contained in the barrage comments. It visualizes, obtains the emotional characteristics and trends of online videos, and makes the best decision. Explore development opportunities.
2.4 Product market positioning
The advantage of this product is that it is different from the current mainstream sentiment analysis products. It has added an audio bullet screen sentiment analysis module. The analysis module is based on the sentiment value assigned by the user. It can complete the current mainstream tasks while leading the current technology or leading the new technology. 's arrival With the support of Mango TV's own powerful data, it can well show the characteristics of the product. For Mango TV's entertainment communication and media communication, it can get the latest direction in time, and increase the ratings and other requirements of the demand side in time. It can be seen that this product, as a subsidiary product of Mango TV's main team product, is imminent, and it has full value whether it is developed internally or externally.
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3 product development plan
3.1 Product development blueprint
"Sentiment classification" is not easy to design products for pure goals. The advantage of this task is that the threshold is low, but the disadvantage is that competition is fierce. Therefore, creativity and inspiration are often more important. Sentiment analysis is more suitable as a project. Sentiment analysis is only a part of sentiment analysis, and eventually it has to be incorporated into a multi-functional, all-round large product, which can quickly understand the social evaluation of the company or other related functions.
3.2 Product version planning
Development plan: The traditional bullet screen sentiment analysis module is completed in the early stage, and the two major modules are analyzed according to the sentiment value assigned by the user to meet the current application requirements. The mid-term plan is to complete the audio bullet screen sentiment analysis module, and the later plan is to merge into the large product platform. Realize the key link of barrage sentiment analysis and integrate it into the whole link to increase the value of work.
Prominent advantages: In the early and mid-term, the analysis module is based on the sentiment value assigned by the user. Free and large-scale realization of the barrage sentiment analysis. This is the product advantage and highlight in the early and mid-term. The later avant-garde technology is incorporated into the audio barrage sentiment analysis, which will push the product To another new journey.
4. Product development planning
4.1 Demand analysis
For details, please see the product requirement analysis document
4.2 Product design
4.3 R&D plan
5 Marketing Planning
5.1 Product launch plan
5.2 Product Manual
5.3 Marketing
6 Feasibility analysis
6.1 Product competitiveness analysis
6.2 Resource requirements and guarantee capabilities
6.3 Risk analysis and countermeasures
6.4 Economic Benefit Analysis
6.4.1 Product production cost analysis
6.4.2 Project product pricing
6.4.3 Expected production scale and sales volume of products
6.4.4 Analysis of expected economic benefits
7 summary
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