The Construction and Evolution Trends of Media Ecology Under

Artificial Intelligence Technology System

Ying Yu

and Zicun Zhao

Shenyang jianzhu university Institute of Design and Art, Hunnan, Shenyang, Liaoning, China

Keywords: Artificial Intelligence Technology, Media Ecology, Ecological Evolution, Production Process.

Abstract: The development of artificial intelligence technology has provided external technical conditions for the

construction of communication ecology. The media industry has gradually started to use intelligent technology

for content change and structure optimization, and has adopted data processing and machine algorithms to

realize the "intelligence + intelligence" transformation of the media ecology. This paper analyzes the

application of artificial intelligence technology in the media field, discusses the evolution trend of media

ecology driven by technology, and puts forward suggestions for the integration and development of media

industry and artificial intelligence technology.

1 INTRODUCTION

Artificial intelligence technology plays an important

role in the media field based on Internet of Things

technology, artificial intelligence technology and big

data technology, laying the foundation for the

evolution of media ecology in the underlying

architecture and realizing the optimization of media

production factors and communication factors.

Artificial intelligence technology provides a high-

quality environment for the development of the media

industry and poses new challenges to the

development of the media field. How to achieve

technological integration on the basis of existing

media business and meet the personalized needs of

audiences should attract great attention from related

fields.

2 THE CURRENT STATE OF

APPLICATION OF ARTIFICIAL

INTELLIGENCE

TECHNOLOGY IN THE MEDIA

FIELD

Artificial intelligence technologies cover a wide

range of fields. Artificial intelligence technologies

applied to the media sector include intelligent data

https://orcid.org/0000-0003-4111-0882

analysis technologies, logic control technologies, and

virtual scene construction technologies. For example,

in 2016, China started to experiment with the

application of intelligent robots to edit news

documents and write copy content according to

grammar and logic. The quality of the content can be

guaranteed. This technology is achieved by applying

logic control technology based on artificial

intelligence technology. After the intelligent content

creation is completed, the application based on data

analysis technology can intelligently push the content

and accurately analyze the needs and behaviors of

users. In the process of live broadcast and program

building, virtual scene construction technology uses

intelligent signing and scene splicing to improve

viewers' experience of the program. The application

of artificial intelligence technology in the media field

takes various forms and has a great impact on the

evolution of the media ecology, both for the accuracy

and scientific dissemination of information, but

"pirated articles", "black box operations", "narrow

push of information", "scripts", and how to establish

a green and high-quality media ecological

environment in the field of media control according

to the current evolution of the media ecology is

particularly important. (Ma. 2022)

https://orcid.org/0000-0003-4718-265X

532

Yu, Y. and Zhao, Z.

The Construction and Evolution Trends of Media Ecology Under Artiﬁcial Intelligence Technology System.

DOI: 10.5220/0011915300003613

In Proceedings of the 2nd International Conference on New Media Development and Modernized Education (NMDME 2022), pages 532-536

ISBN: 978-989-758-630-9

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

3 THE EVOLUTION TREND OF

MEDIA ECOLOGY UNDER

ARTIFICIAL INTELLIGENCE

SYSTEM AND DESIGN

METHOD

3.1 Changes in the Structure of

Communications: Development

into the Field of Integrated

Intelligence

The application of artificial intelligence in the media

field has provided great convenience for program

production and news gathering, and has shown a

development from professional intelligence to

comprehensive intelligence in the communication

structure. The working atmosphere and work

efficiency in the media field have been rapidly

improved, and the trend of industrialization has been

observed. The evolution of the communication

structure to the field of integrated intelligence has led

to a gradual increase in the industrialization of the

media. The total scale change of media industry from

2017 to 2021 is shown in Table 1.

Table 1: Total Scale of Media Industry from 2017 to 2021

(RMB 100 million Yuan)

particula

r yea

2017 2018 2019 2020 2021

Total

value of

-pu

19506.

21571.

24140.

26168

2971

0.3

Rate of

rise (%)

15.69 10.58 11.91 8.4

13.5

According to the content analysis in Table 1,

artificial intelligence is mainly applied in the media

field to promote the industrialization of media, and

the total output value shows a year-on-year increase

in the development trend. This is due to the

comprehensive intelligent direction of the

transformation process of the communication

structure of the obvious optimization of stylized

writing can reduce more than 20% of the editing time,

automatic generation technology can reduce more

than 30% of the working time, media staff can devote

more energy to further content. In addition, artificial

intelligence as the announcer and announcer of news

programs, technicians report the news through

environment building and character building,

increasing the experience and live sense of the

program. Under the artificial intelligence system, the

integration of technology and content is gradually

realized in the communication structure from the

original programmed writing to the creation of offline

visual content, and the development from the original

professional intelligence to comprehensive

intelligence has promoted the industrial evolution and

structural evolution of the media ecology. (Zhang,

Liu. 2021)

3.2 Changes in Communication

Technology: Efficient Factor

Production Processes

3.2.1 Content is the Core of Media

Production

The application of artificial intelligence technology

in the media field has realized changes in the

production factors, becoming more efficient in

content production, showing dynamic changes in the

production process and shifting to the direction of

"user production + professional production". Under

the new production model, the media form in the

media field has changed significantly, as shown in

Table 2.

Table 2: Changes of Media Form of the Media Industry

from 2017 to 2021

A particular

yea

2017 2018 2019 2020 2021

Internet

traffic (one

illion GB)

245.9 711.1 1220 1656 2216

APP quantity

(ten

thousand)

252 345 367 403 453

Number of

movies (ten

thousand)

41179

5077

6007

6978

7558

Number of

TV programs

(ten

thousand)

1414 2446 2654 2874 3021

As can be seen in Table 2, changes in

communication technologies have led to an evolving

media landscape, with Internet users gaining access

to more content and information. The data analysis of

artificial intelligence technology and the collection of

user data through big data technology have led to

more accurate content dissemination in the media

field, and users have become producers and creators

of media content. The application of powerful data

collection and data analysis functions of big data

technology and media content creation through

programmed settings has led to a continuous growth

and prosperity of the self-publishing form.

The Construction and Evolution Trends of Media Ecology Under Artiﬁcial Intelligence Technology System

533

3.2.2 Artificial Intelligence Big Data

Analysis process

In terms of artificial intelligence big data analysis

technology, the analysis demand gradually changes

from statistical mining analysis of small-scale,

single-source, single-modal data to complex

heterogeneous correlation of massive, multi-source,

multi-modal data. The rapid development of deep

learning technology has driven the improvement of

big data analytic model capability. Neural network

models returned to the limelight after winning the

2012 ImageNet competition, a target recognition

project for computer vision, and subsequently gave

birth to a series of groundbreaking work, including

knowledge graphs to provide knowledge services,

generative adversarial networks to synthesize real

data, and GPT-3 pre-trained language models. In

addition, increasingly mature deep learning

frameworks (such as TensorFlow, PyTorch, and

Flying Paddle) have lowered the barrier to using deep

learning to analyze big data. (Cheng, Liu, Zhang.

2022)

As shown in Figure 1, the artificial intelligence

big data analysis process atmosphere two steps, the

software tool layer in the application process to

achieve a comprehensive combing of data collection

functions, and the collated data for in-depth analysis,

and finally the modular matching content generation

for the application layer to achieve personalized

media content customization. In this process, the

media industry ecology shifts in the direction of

efficient production processes, and the potential of

technology in the development of media

industrialization and scale is tapped. At present, the

media field is also more inclined to personalization

and customization in content production,

disseminating content according to the preferences of

the public, so that the massive amount of information

in the media field provides accurate services for users

and realizes the creation of a large-scale and

personalized media content dissemination ecology.

Figure 1: Artificial Intelligence Big Data Analysis Process

Architecture

3.3 Change in Values: Total

Management of Technical Content

3.3.1 Content is the Core of Media

Production

From the perspective of the evolution of the media

ecology, the development of artificial intelligence is

mainly reflected in the concept of communication.

The editorial staff is the reviewer and disseminator of

content, assuming the right to gate-keeping decisions

in the development of the media, playing the main

role in the planning, production and dissemination

process, and needing to control the dynamics of the

program in the live program. In this environment, the

communication concept of media people has

changed, making the media ecology change to the

direction of integrated management of technical

content. In the evolution from the original content

construction to integrated management, while

reducing the work pressure of the personnel involved,

it also places higher demands on media people. The

following is a table of the application of AI

technologies in program construction from 2017 to

2021. (Zhang, Gong. 2020)

Table 3: Artificial Intelligence Programs from 2017 to 2021

particular

yea

2017

201

2019 2020 2021

Virtual

Studio (all)

1 5 12 18 24

Smart

article push

(ten

thousand

pieces)

1544

254

8415

125412

16334

Virtual

anchor (all)

0 2 8 10 13

Program

format (all)

2 12 18 24 28

According to the content analysis in Table 3, the

number of artificial intelligence programs gradually

increases from 2017 to 2021, and the forms that

appear are more diverse. Under the artificial

intelligence system, the media ecology gradually

changes in terms of value concept, and technology

and content become the main means of media content

construction and dissemination.

3.3.2 Structural Design

In terms of artificial intelligence big data processing

technology, there are many different parallel

computing models depending on the processing

requirements, including batch processing represented

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534

by Hadoop and Spark, high real-time stream

processing represented by Spark Streaming, Flink,

STORM, stream batch hybrid processing represented

by Apache Beam and Lambda, and graph processing

represented by GraphX and Apache Giraph. and

graph processing represented by GraphX and Apache

Giraph.

Tall array is a new mode of operation provided by

Matlab program to cope with big data analysis. tall

array means to represent all the data in the form of

column vector first, to create a long column vector

with one column for each parameter, in the process of

programming algorithm not all the values of the

vector, only the first few data, other data with "? "

This means that these data are not put into memory

during the programming process and the computer

does not know the amount of data in the column array.

In the subsequent calculation, when calling the tall

array, using the algorithm to calculate all the data, the

tall array will be in the form of a stream calculation,

read a section of data, calculate and process this

section of data, and then read the next section of data,

access, read, and process a large collection of data in

sections, until all the tall array data is traversed,

complete the calculation, and summarize the output

of the value requested by the operation command.

When using a single computer, you can use the

Matlab Parallel Computing Toolbox to call multiple

CPUs to process operations simultaneously, and

when processing in a cluster, you can also use the

Cluster Parallel Computing Toolbox, which can

optionally call all available CPUs and memory in the

cluster to process the data, which can greatly improve

the computing power and increase the operation

speed by This can greatly increase computing power

and run more than 3 times faster. (Cui, Ma, Zhang.

2020)

Figure 2: Workflow Based on Big Data Artificial

Intelligence Technology

As shown in Figure 2, the workload of the media

is reduced based on big data artificial intelligence

technology, and the work pressure of the writers and

directors is gradually reduced. Especially in the

process of building virtual studios and shaping virtual

characters, the dissemination of programs can be

accomplished by the modular adjustment of

technicians.

4 MEASURES ECOLOGY

CONSTRUCTION MEASURES

UNDER ARTIFICIAL

INTELLIGENCE SYSTEM

4.1 Create High-Quality Intelligent

Content

The creation of high-quality intelligent content can

increase the audience's live experience of the

program and make the audience have a different

program experience. In the process of building text

media content, it can also realize personalized and

accurate content pushing, which meets the interests

of the audience. Therefore, the construction of media

ecology should focus on the creation of high-quality

content and realize the simultaneous innovation and

development of content and technology in the

construction of media ecology.

4.2 Policies to Promote Cross-Border

Integration

In order to further deepen the application of artificial

intelligence in the media field and play its role in the

construction of media ecology, China should create

major projects through policy guidance. The

hardware facilities and software technologies in the

media field have shown the development trend of

continuous development and progress, and the media

ecology is evolving in the direction of technology and

integration, which makes the media field play a

driving role in the perspective of content

dissemination, structure optimization and value

change.

4.3 Improving the Construction of

Laws and Regulations

Although the application of artificial intelligence in

the media field has promoted the development of

media ecology, audiences also question whether there

are ethical and legal issues in the application of data

analysis, personalized recommendation and artificial

intelligence technologies. There is a need to provide

The Construction and Evolution Trends of Media Ecology Under Artiﬁcial Intelligence Technology System

535

a good external environment for the construction of

programs in the media field by improving legislation

to promote the in-depth development of the media

industry, thus building a good media business

environment.

4.4 Strengthen the Introduction of

Technical Talents

The development of media industry under artificial

intelligence technology, relevant practitioners need to

have media knowledge and a deep understanding of

communication theory, and also deal with a deep

understanding of artificial intelligence technology in

order to complete the creation of quality programs

with the support of software and hardware.

5 CONCIUSION

To sum up, the media ecology driven by artificial

technology is gradually developing to the perspective

of comprehensive intelligence, deep integration and

comprehensive governance. Relevant media subjects

should pay high attention to the integration

application of artificial intelligence technology in the

media field, and China should also tap into the

integration measures of artificial intelligence

technology and media field to promote the benign

evolution of media ecology through content

intelligence, policy project-based implementation,

standardized legislation on content intelligence, and

strengthening the introduction of intelligent

technology talents.

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