applied
sciences
Article
Identification of Opinion Leaders and Followers—
A Case Study of Green Energy and Low Carbons
Chun-Che Huang 1, Wen-Yau Liang 2,*, Po-An Chen 1and Yi-Chin Chan 3
1Department of Information Management, National Chi Nan University, Pu-Li 54561, Taiwan;
cchuang@ncnu.edu.tw (C.-C.H.); annieab.chen@gmail.com (P.-A.C.)
2Department of Information Management, National Changhua University of Education,
Changhua 50074, Taiwan
3Program in Strategy and Development of Emerging Industries, National Chi Nan University,
Pu-Li 54561, Taiwan; s106245903@mail1.ncnu.edu.tw
*Correspondence: wyliang@cc.ncue.edu.tw
Received: 21 October 2020; Accepted: 24 November 2020; Published: 26 November 2020
Abstract:
In recent years, with the development of Web2.0, enterprises, government agencies,
and traditional news media, which have been positively influenced by opinion leaders, have been
dedicated to understanding leaders’ opinions on the web in order to seek convergence. Specifically,
with the increase of environmental awareness, the introduction of green energy and carbon reduction
technology has become an important issue. Consequently, studies identifying opinion leaders and
followers who are interested in green energy and low carbon have become important. This study
aims to find a solution that can identify the characteristics of opinion leaders and followers that can
be widely used, which will help certain public policies or issues to be more effectively disseminated
in the future. To model the characteristics of opinion leaders and their influence on followers,
this study uses a dual matrix. The interaction patterns are recognized among opinion leaders and
followers, with the aim of developing public policy to promote green energy and low carbon emissions.
A case is studied to validate the superiority of the proposed solution approach. With the proposed
approach, a (business) organization can identify and access opinion leaders and their followers.
Through communication, these organizations can absorb strain and preserve functions despite the
presence of adversity. This study also clearly demonstrates its contribution and novelty through
comparisons with the existing alternative method.
Keywords:
green energy and low carbon; opinion leaders; followers; social media; matrix method;
intelligent systems
1. Introduction
With the rise of communication technology, people are utilizing platforms such as content
sharing sites, blogs, social networking, and wikis to create, modify, share, and discuss Internet
content. Social media provides flexible platforms that play key roles in energizing collective action in
movements [
1
]. This represents the social media phenomenon, which can significantly impact society
and industry, e.g., firms’ reputations, sales, and even survival [
2
]. Within the discussions on social
media, certain individuals influence others and thus emerge as opinion leaders. Opinion leaders have
great impacts and influence on social media. Organizations can take advantage of these predispositions
through marketing research and public relations, nurturing opinion leaders or advocates, placing and
creating advertisements, developing new products and lowering the cost-to-serve [
3
]. On the Internet,
the power of these leaders is increasing larger and sequentially influencing entire societies through
Appl. Sci. 2020,10, 8416; doi:10.3390/app10238416 www.mdpi.com/journal/applsci
Appl. Sci. 2020,10, 8416 2 of 16
calls to protest, promotion of policy and decision-making, which was defined as the fifth right in the
“Towards a Civil Society” seminar [4].
The world must confront the energy crisis and air pollution. Discussions about energy issues are
increasing. These discussions range from nuclear energy, thermal power, hydropower, and other forms
of green energy and low carbon technology, including wind, solar, tidal, and biomass geothermal
energy issues. In Taiwan, whenever an energy crisis occurs, energy charges increase. Anti-nuclear
positions and other energy issues are discussed broadly. Therefore, the Taiwan government tries to
understand people’s needs and questions.
On the Internet, the roles of opinion leaders and followers in the formation of these issues cannot
be neglected. According to the “theory of two-step flow” [
5
] and Rosen’s definition of opinion leaders’
characteristics, “social media initially pass the information to opinion leaders, then opinion leaders
spread the information to followers and influence their attitudes” [
6
]. Thus, when followers follow
opinion leaders, the formers’ judgments and attitudes will be influenced and changed by opinion
leaders. This study defines opinion leaders as people or social media with high social status who
are able to influence followers. This study defines followers as the users who follow certain issues,
publish related discussions and add their own ideas. They spread, repost or blindly follow the
behaviors of opinion leaders.
Most previous research of opinion leaders focuses on the commercial domain rather than on
nonprofit-related policies such as energy policy [
7
]. In the promotion of many public policies through
online postings, it is difficult to clearly identify opinion leaders and followers, which greatly reduces
the effectiveness of communication. Based on the community attributes of opinion leaders and whether
they can successfully resonate, this study aims at providing a method to try to identify who are
opinion leaders or who are likely to become opinion leaders in social media, and who are followers.
Relational matrix analysis is used to represent the relationship between opinion leaders and followers
in social media and to identify the collection of opinion leaders and potential opinion leaders.
Furthermore, previous studies [
8
] have used quantitative methods of analysis. One example is the
SuperedgeRank algorithm. However, this algorithm not only has difficulty identifying potential opinion
leaders effectively but also neglects how opinion leaders influence followers and how relationships
between opinion leaders and followers are characterized. It also ignores the increasingly important
role played by intelligent systems such as algorithms.
Although the literature on green energy is rapidly increasing, many studies suggest that this
problem needs to be dealt with by considering a broader perspective [
9
]. This study not only examines
the issue from the perspective of intelligent systems such as algorithms but also identifies the roles
of opinion leaders and followers on social media in relation to the introduction of green energy and
carbon reduction technology, with the aim of developing public policy to promote green energy
and low carbon emissions. This study is novel not only because it takes quantitative factors and
tradition clustering approaches into account but because it also analyzes posts, poster characteristics
and their interactive relationships on social media. This study reviews relevant literature in Section 2.
In Section 3, we propose a method to identify opinion leaders and their followers based on their
interactions on social networks. The interaction patterns are also identified. An energy case is studied
in Section 4to validate the proposed solution approach and enhance communication effectiveness
between government policymakers and people’s desires. The discussion is summarized in Section 5,
and Section 6concludes this study.
This research contributes to finding a solution to easily identify the characteristics of opinion
leaders and followers in the case of online posts related to green energy and low-carbon policies.
Once certain public policies need to be effectively disseminated, they can be widely used. Using the
same model and the solution approach, the results of this study can be extended from the green energy
low carbon issue to other social issues. Furthermore, this study provides a new perspective to deal with
the effective identification of opinion leaders and followers, at the same time, promotes the “theory of
two-step flow” to add another research perspective in the academic field.
Appl. Sci. 2020,10, 8416 3 of 16
2. Literature Review
2.1. Green Energy and Low Carbon
Global warming, unexpected climate change, dwindling energy resources and unprecedented
amounts of air pollution have become critical problems. The United Nations’ 2030 Sustainable
Development Goals show that a sustainable modern electricity grid [
10
], reduction of CO
2
emissions [
11
]
and the carbon footprint of human mobility to a sustainable level [
12
] etc., are key parts. In addition,
exhaustion of fossil fuel is viewed as a big challenge of human development [
13
] since energy is
an expensive resource that is becoming more scarce with increasing population and demand [
14
].
Green energy could help governments reduce the dependency on energy importation, improve the
variety of production resources and advance sustainable environmental development. Moreover,
the usage of rich green energy could benefit economies significantly [15].
In the past, studies of green energy and low carbon have focused on issues of energy itself and
energy systems, for example, integration of energy systems [
16
], reliability of the power distribution
system [
17
], uptake of biomass energy [
18
], and so on. Few studies have focused on social opinions
about green energy and low carbon. In recent years, due to awareness of the environment, the public
has started to care more about the environment and quality of life [
19
]. Social media has strengthened
community among people and emerged as a platform to spread messages quickly and powerfully.
In the era of Web 2.0, massive public opinion is increasingly generated on the Internet [
20
]. Therefore,
the study of the role of social media in green energy and low carbon social issues is very important.
2.2. Opinion Leaders
In the era of the Internet, opinion leaders enhance content sharing. In fact, almost all of the content
is generated by opinion leaders (the 90–91% law) [
21
]. What makes opinion leaders so important
on social networks is their ability to informally influence others’ attitudes and behaviors [
22
–
25
].
Opinion leaders usually have access to far more information on a certain topic and have professional
experience with the topic. Rosen defined the characteristics of opinion leaders proposed the acronym
ACTIVE. ACTIVE stands for the six characters of opinion leaders: ahead in adoption, connected,
travelers, information-hungry, vocal, and exposed to the media [6].
In a recent qualitative survey carried out through focus groups, Katz and Lazarsfeld proposed the
“theory of two-step flow” in 1995 and pointed out that opinion leaders are situated between social
media and the majority of people. The information first reaches the opinion leaders or influencers [
26
],
who then introduce it to the wider population [
5
]. Followers are those who are affected and change
their behaviors and attitudes when receiving the information [
27
]. The followers are enormously
influenced by opinion leaders in terms of changing their attitudes and behaviors [25].
Based on the above study, we elaborate on the attributes of opinion leaders as follows: Their life
experience and understanding of knowledge are rich and thorough and a majority of them are
highly educated. Moreover, they have strong social skills, strong connections with the broad masses,
and good reputations due to their professionalism and knowledge. They have great influence and
appealing power. They exhibit sensitivity to information, willingness to accept new things and an
innovative spirit.
2.3. Opinion Leaders Identification
Many theories have been put forward about social networks, but few address the issue of opinion
leader identification [
28
]. According to a previous literature review, opinion leaders are simply
determined based on some visible user activities, and other factors that allow a user to become an
opinion leader are ignored [
28
,
29
]. Studies of Internet opinion leaders have also mainly focused
on the role of Internet opinion leaders in spreading the news and in the Internet world of word
mouth marketing [
23
]. Consensus has not yet been reached in the analysis of Internet opinion
leaders. Few efforts have been taken to create a computer-based model to identify and analyze the
Appl. Sci. 2020,10, 8416 4 of 16
opinion leaders in an Internet community, and the studies that have been undertaken on this issue
have failed to reach an in-depth level [
30
]. At present, studies related to the TwitterRank algorithm
based on PageRank [
29
] and the contribution of information to InfluenceRank [
31
] and weighted
Page-Rank [
32
] make use of the network construction of user interaction, but they neglect the users’
inherent features [33].
In addition, from the perspective of data mining, the identification of opinion leaders is a
cluster problem. However, the aforementioned studies consider the relationships of people to be
a social network. Engagement is used as an effective degree to measure user interaction with an
organization. Basic interactions include commenting on contents, sharing contents, or “liking” or
“favoriting” content. A core KPI for social media is that engagement is high, as this would indicate
that organizations are producing content that users find interesting enough to spend additional time
on [
34
]. Unfortunately, when applying the cluster problem to social networks, previous studies have
only taken quantitative factors, and traditional clustering approaches into account, e.g., support vector
machines [
35
], k-means [
36
], partitioning around medoids [
37
], fuzzy c-means [
38
], and so on have
been used to resolve quantitative clusters. However, qualitative characteristics are not yet considered,
and only static data have been analyzed. To study the qualitative characteristics of opinion leaders
and the impact of opinion leaders on followers, [
39
] evaluates whether every speaker in social media
satisfies the characteristics of an opinion leader. By observing the relational matrix, the interacting
relations between users in social media are analyzed, and opinion leaders and followers are identified.
However, there are no theoretical background axioms implied in [
39
], specifically from the perspective
of communication to validate the results.
2.4. Opinion Leaders Identification Algorithms
Ma and Liu [
40
] used the SuperedgeRank algorithm to analyze the attributes of three seed networks
and identify opinion leaders on the Fukushima nuclear issue. In another study, Jiang et al. [
41
] designed
and implemented a BBS opinion leader mining system based on an improved PageRank algorithm
using MapReduce. Ziyi et al. [
30
] adopted the core algorithm of the Internet searching–PageRank
model and, by combining the analysis of the influence of linguistic data and sentimental preference,
put forward a method to identify Internet opinion leaders; they also verified the method by carrying
out an empirical study. Cheng et al. [
42
] combined influence with sentimental analysis based on the
content of posts and filtered opinion leaders by combining the PR values of the PageRank algorithm
and recognition degree, abbreviating the IS Rank algorithm. Deng et al. [
43
] constructed a SINA
Micro Blog APIs based Micro Blog crawling and analysis tool, and a node betweenness approximation
computation method was proposed, offering better accuracy and less running time to detect core
opinion leaders on Micro Blog graphs.
PageRank is an excellent sorting algorithm, but its running speed decreases significantly with the
increase of the number of data nodes. Jing and Lizhen [
33
] proposed a hybrid data mining approach
based on user features and interaction networks, which includes three parts: a way to analyze users’
authority, activity and influence, a way to consider the orientation of sentiment in an interaction
network and a combined method based on the HITS algorithm for identifying microblog opinion
leaders [
33
]. Chu et al. [
44
] researched social networks to access the influence of tobacco opinion
leaders on followers and found that followers are a vulnerable group. They are young and low
educated. Followers are easily influenced by opinion leaders. Therefore, anti-smoking education to
stay away from tobacco can educate them on social media. Obviously, opinion leaders on the Internet
have considerable influence on followers, and opinion leaders are often used in marketing in the
e-commerce industry. The research of Lin et al. [
45
] found that opinion leaders can use their influence
to act as important promoters of products and services. It is recommended that companies or corporate
managers choose to cooperate with opinion leaders of a certain type of forum to promote products
or services. What is the impact of the levels of followers’ trust in opinion leaders on the resulting
influence? Zhao et al. [
46
] used opinion dynamics theory to study the influence of trust in opinion
Appl. Sci. 2020,10, 8416 5 of 16
leaders. His research found that followers’ trust in opinion leaders determines opinion leader influence.
It is suggested that if the communication effect of e-commerce is pursued, the key premise can increase
the trust of opinion leaders.
Not only have many studies investigated opinion leaders in the e-commerce field, but the
role and function of opinion leaders have attracted attention in politics and the public domain.
Aleahmad et al. [43]
examined the political field by proposing the effective OLfinder algorithm.
The researchers found that this algorithm can not only find opinion leaders in social networks but
also calculate their popularity. Many people are curious about why opinion leaders like to play the
role of opinion leaders. Winter et al. [
47
] examined people who disseminate opinions about politics or
public affairs on the Internet and identified these people as opinion leaders who try to influence the
psychological motivations and personality characteristics of followers. This study found that opinion
leaders have strong psychological motivations to actively express themselves and persuade others,
making them like to play the role of opinion leaders. In addition, in social network analysis, centrality
methods have been applied to measure the importance of nodes in a network whereby nodes with
higher centrality can influence others more significantly [48,49].
All in all, past relevant research either used a certain social measurement method based on
interview self-reports or questionnaire surveys or used quantitative clustering techniques to identify
opinion leaders. Few studies have actually investigated online posts to identify opinion leaders and the
social patterns of interaction between opinion leaders and followers. Thus, it is important to propose a
method to analyze posts, posters’ characteristics and their interactive relationships in social media.
3. Methodology
