DOI: https://doi.org/10.21203/rs.3.rs-2627262/v1
Sports play an important role in daily life. Every year, thousands of people watch sports events on TV or on the Internet, in which football events attract more attention. The performance of a team may have a huge impact on its fan loyalty. Therefore, the purpose of this study was to explore whether the performance of a team will affect the loyalty of fans, and how to affect the loyalty of fans. Applying web crawler to collect spectators’ comments on the performance of the Chinese Men's National Football Team in the 2022 FIFA World Cup Qualification, word frequency analysis, semantic network analysis and emotional analysis on these comments, it was concluded that the factors that affect fan loyalty from high to low were: fan attitude loyalty factor, fan identity factor, fan behavior loyalty factor, fan satisfaction factor. It was believed that this study could provide a reference for managers to improve fan loyalty.
A large number of football matches are held in China every year, and thousands of people watch football matches on TV or on the Internet, thus forming a large group of fans (Mays, 2012). Fans provide emotional and behavioral support to the team by watching football matches, which forms the loyalty of football fans (Funk & James, 2001). Generally speaking, the formation of fan loyalty goes through four stages: cognition, attraction, recognition and loyalty (Oliver, 1999). At present, the researches on fan loyalty are mostly divided into two aspects: attitude loyalty and behavior loyalty (Bee & Havitz, 1999). Attitude loyalty indicates fans' recognition and preference for teams or players, while behavior loyalty indicates fans' long-term support for teams or players (Kang, 2017).
In the study of football matches, team performance can be evaluated by match rankings, game points, winning games and the number of goals scored (Arnason et al., 2004; Dauty & Collon, 2011; Hagglund et al., 2013; Eirale et al., 2013). Team performance will affect the loyalty of the fans to the team. When the team does not perform well in the game, it leads to a decline in the fans’ loyalty (Tapp, 2004). Team performance is affected by players’ salary, the technical and tactical level of the players, the injuries of the team, the reform of team management and other factors (Anthony & Norman, 2017). With the development of football clubs and leagues becoming more and more commercial and professional, having stable and loyal fans is an important competitive advantage of a team (Bauer et al., 2008). The fans’ overall satisfaction with the team's performance affects their willingness to watch the game, and then affect their loyalty (Wakefield & Sloan, 1995; Laverie & Arnett, 2000). Successful performance of a team enhances the fans' willingness to watch the game and their loyalty, while the failure gives the opposite effect (Hansen & Gauthier, 1989; Matsuoka et al., 2003).
In the past, the researches on fan loyalty are mostly carried out through questionnaires (Kaelberer, 2016; King, 2000; Patrick, Michael, & Beeto, 2010), however, the recovery efficiency of questionnaires is low, and the validity of the data is often difficult to guarantee. With the popularity of the Internet and the rapid development of information technology, online comments have become a convenient and effective way to obtain data (Fang, 2019). Through online comments, fans can share their views on the team's performance and express their subjective feelings, so as to measure (or reflect) fans' loyalty to the team (Al-Smadi, Qawasmeh, Al-Ayyoub, Jararweh, & Gupta, 2017; Ray, Smith, & Fowler, 2016). Therefore, online comments are also seen as a way to maintain fan relationships and enhance fan loyalty (Watkins & Lee, 2016). The satisfaction of online comments can be obtained through high-frequency words, semantic network analysis and emotional analysis (Shao, Chang, & Morrison, 2017). High-frequency words refer to the words with high frequency in comments, and the focus of commentators' attention can be reflected by high-frequency words. Through the connection between words and words, semantic network can show the logical and causal relationship between words (Sowa, 1991). Emotional analysis was first put forward by Pang and others (Pang, Lee, & Vaithyanathan, 2002), by dividing the commentator's language into positive, negative and neutral, making emotional analysis and judgment, and then finding the commentator's emotional tendency. More valuable information can be obtained through the prediction of this emotional tendency (Wang et al., 2013). Emotional analysis is a commonly used data analysis method in recent years. Through the analysis of online comments, we can find out whether the comments express positive emotions or negative emotions. Emotional analysis can help researchers better understand the determinants of fan loyalty. To some extent, positive comments represent higher fan loyalty, while negative comments represent lower fan loyalty (Yoon, Petrick, & Backman, 2017).
The FIFA World Cup is the largest and most famous football match in the world (Depetris-Chauvin, Durante, & Campante, 2020). Participating in the World Cup can not only enhance the exposure of teams, players and coaches, but also enhance the loyalty of fans and show the image of the team (Stone & Rod, 2016). Although the performance of the Chinese Men's National Football Team has not been very satisfactory for a long time, the Chinese government still attaches great importance to the development of football projects, and Chinese fans' attention to the FIFA World Cup has not declined. It is the common wish of fans for the Chinese Men's National Football Team to return to the FIFA World Cup (Zhang & Xu, 2019). There are four qualifying places in the Asian Division of the 2022 FIFA World Cup Qualification. In the whole process of qualifying, the Chinese Men's National Football Team ranked second in the group and successfully advanced to the top 12 of the Asian region with an excellent performance of 8 games, 6 wins and 19 points.
The excellent performance of the Chinese Men's National Football Team in the group stage of the 2022 FIFA World Cup Qualification shows fans the hope that the Chinese Men's National Football Team can qualify for the 2022 FIFA World Cup, which helps to enhance the loyalty of the fans to the team.
Therefore, taking the 2022 FIFA World Cup Qualification (Asian Division) as an example, this paper crawls fans' online comments on the performance of Chinese Men's National Football Team on social media (mainly MicroBlog and HUPU) on social media. Big data analysis method is used to explore the impact of the performance of the Chinese Men's National Football Team on fans' loyalty. In addition, through this study, we can also understand the current situation of loyalty of Chinese Men's National Football Team fans, so as to provide a reference for the government to formulate relevant policies in the future, and better improve the performance of the Chinese Men's National Football Team.
Take the performance of the Chinese Men's National Football Team in the 2022 FIFA World Cup Qualification as an example.
In this paper, "Micro-blog" and "HUPU" are selected as data sources. Use Python to crawl all the comments on the performance of the Chinese Men's National Football Team in the 2022 FIFA World Cup Qualification on these two websites. A total of 2352 comments. Because the network data will be updated in real time, only all comments before July 15, 2021 are collected, and follow-up comments are not included in this study.
Pre-process the existing data before data analysis:
Convert traditional characters to simplified characters for later data analysis.
Synonym substitution. Replace "Chinese football" with "Chinese Men's National Football Team", replace "wulei" with "Wu Lei", replace "planning" with "domestication" and so on.
Delete meaningless comments. Some users use a large number of repetitive words to make comments, such as "come on". In order to ensure the accuracy of the data analysis, only one group of "come on" is retained, while there are some meaningless comments such as "Yes", "Oh" and so on. Delete it directly. Finally, 2317 pieces of valid data were obtained, totaling 55824 words.
After the above data are processed, ROST CM is used for word segmentation, word frequency statistics, semantic network diagram and emotion analysis. In order to ensure the accuracy of word segmentation, special words such as "Chinese Men's National Football Team" and "domestication" are added to the ROST CM word segmentation dictionary. In addition, although some high-frequency words appear many times, they have no practical meaning, such as "then", "anyway" and so on, so they are not included in the word frequency statistics.
After using ROST CM to count the high-frequency words, we use Netdraw to build the semantic network graph. Semantic network graph can show the relationship between high-frequency words more directly. In this paper, ROST CM is used for emotional analysis. The emotional value of ROST emotional analysis shows that more than 0 is a positive emotion, less than 0 is a negative emotion, and equal to 0 is a neutral emotion. The closer the emotional value of the positive emotion is to 0, the lower the positive emotion is, the higher the positive emotion is, the higher the positive emotion is; the closer the negative emotion is to 0, the lower the negative emotion is, and the lower the negative emotion is, the higher the negative emotion is. The positive emotion shows that the comment is a comment with high satisfaction, which represents the high loyalty of the fans; on the contrary, the negative emotion shows that the comment is a review with low satisfaction, which represents the low loyalty of the fans (Gavilan, Avello, & Martinez-Navarro, 2018; Almeida & Ramos, 2012). ROST CM is more suitable for the analysis of Micro-blog reviews, which is more consistent with the data sources of this article, so we use this tool for analysis in order to better understand the emotional tendencies of the reviewers.
According to the previous research of scholars (Oliver, 1980; Matsuoka, Chelladurai & Harada,2003; Gladden & Funk, 2010), this paper divides the factors that affect fan loyalty into: fan identity, fan satisfaction, fan attitude loyalty, fan behavior loyalty, and carries on the follow-up emotional analysis according to these four dimensions.
In this paper, a total of 2317 valid online review data were obtained through web crawlers. Among them, there are 779 fan identity factors, 203 fan satisfaction factors, 962 fan attitude loyalty factors and 1217 fan behavior loyalty factors.
Import the obtained data into ROST CM, and finally get the high-frequency vocabulary of the top 50 words, as shown in Table 2.
Influencing factors of fan loyalty |
Concrete performance |
Fan identity factor |
Recognition of the identity of the Chinese Men's National Football Team fans and use this identity in comments |
Fan satisfaction factor |
Comments on the performance of Chinese Men's National Football Team in the 2022 FIFA World Cup Qualification |
Fan attitude loyalty factor |
Comments on positive or negative attitudes towards the current situation and prospects of the Chinese Men's National Football Team |
Fan behavior loyalty factor |
Positive or negative comments on the image of the Chinese Men's National Football Team |
High-frequency word |
Frequency |
High-frequency word |
Frequency |
---|---|---|---|
Chinese Men's National Football Team |
437 |
Play well |
36 |
Men's football team |
245 |
Penalty kick |
35 |
China |
181 |
Play football |
35 |
Player |
158 |
Viet Nam |
33 |
Match |
127 |
Asian Football Confederation |
33 |
Football |
114 |
Unfortunately |
32 |
FIFA World Cup |
93 |
Iran |
32 |
Syria |
88 |
Second |
32 |
Wu Lei |
84 |
South Korea |
30 |
League |
75 |
Strength |
28 |
Japan |
74 |
Congratulations |
27 |
Level |
72 |
Main force player |
27 |
Asia |
70 |
Talent |
27 |
Country |
67 |
Opportunity |
27 |
Maldives |
67 |
Shao Jiayi |
25 |
Team |
48 |
Free kick |
24 |
Qualify |
47 |
Epidemic prevention |
23 |
Football association |
46 |
Deng Zhuoxiang |
22 |
Fans |
45 |
France |
22 |
Problem |
42 |
Australia |
21 |
The Philippines |
41 |
Home court |
21 |
Europe |
39 |
Chinese |
21 |
National team |
38 |
Goal |
20 |
Go abroad |
38 |
Achievement |
20 |
Group |
36 |
Brazil |
19 |
Football-related words can indicate the reviewers' recognition of the identity of fans, and the higher ranking words are "Chinese Men's National Football Team (437)", "China (181)", "Football (114)", "FIFA World Cup (93)" and so on.
Words related to team or field performance can indicate the reviewers' satisfaction, such as "Wu Lei (84)", "Level (72)", "Qualify (47)" and so on.
By using the functions of ROST CM social network and semantic network analysis, this paper makes a semantic network analysis of the reviews on the performance of the Chinese Men's National Football Team in the 2022 FIFA World Cup Qualification. The results are shown in Fig. 1.
It can be seen from Fig. 1 that the person who sends out the most connections is "Chinese Men's National Football Team", that is, the word with the most common occurrence is "Chinese Men's National Football Team". The next most common words are "China", "Player" and "Football", followed by "Japan", "Match", "Country" and so on. Words such as "Asia", "Wu Lei" and "FIFA World Cup" send out fewer connections. The rest of the words with the least number of connections.
As can be seen from Table 3, the reviews on the performance of the Chinese Men's National Football Team in the 2022 FIFA World Cup Qualification are mainly divided into three categories: positive emotion, neutral emotion and negative emotion. Of these, 998 were positive emotions, accounting for 43.07%; 778 were neutral emotions, accounting for 33.58%; and 541 were negative emotions, accounting for 23.35%.
Emotional |
Quantity |
Proportion |
---|---|---|
Positive emotion |
998 |
43.07% |
Neutral emotion |
778 |
33.58% |
Negative emotion |
541 |
23.35% |
Total |
2317 |
100% |
As can be seen from Table 4, there are 381 positive emotions, accounting for 48.91%, 223 neutral emotions, 28.63% and 175 negative emotions, accounting for 48.91%, 22.46%, respectively.
Emotional |
Quantity |
Proportion |
---|---|---|
Positive emotion |
381 |
48.91% |
Neutral emotion |
223 |
28.63% |
Negative emotion |
175 |
22.46% |
Total |
779 |
100% |
As can be seen from Table 5, there are 84 positive emotions, accounting for 41.38%, 69 neutral emotions, 33.99% and 50 negative emotions, accounting for 41.38%, 24.63%, respectively.
Emotional |
Quantity |
Proportion |
---|---|---|
Positive emotion |
84 |
41.38% |
Neutral emotion |
69 |
33.99% |
Negative emotion |
50 |
24.63% |
Total |
203 |
100% |
As can be seen from Table 6, there are 483 positive emotions, accounting for 50.21%, 297 neutral emotions, accounting for 30.87%, and 182 negative emotions, accounting for 18.92%.
Emotional |
Quantity |
Proportion |
---|---|---|
Positive emotion |
483 |
50.21% |
Neutral emotion |
297 |
30.87% |
Negative emotion |
182 |
18.92% |
Total |
962 |
100% |
As can be seen from Table 7, there are 508 positive emotions, accounting for 41.74%, 373 neutral emotions, accounting for 30.65%, and 336 negative emotions, accounting for 27.61%.
Emotional |
Quantity |
Proportion |
---|---|---|
Positive emotion |
508 |
41.74% |
Neutral emotion |
373 |
30.65% |
Negative emotion |
336 |
27.61% |
Total |
1217 |
100% |
It could be seen from Table 2 that the highest-ranking word was "Chinese Men's National Football Team", while other words with fan identity such as "China", "Football", and "FIFA World Cup" were also at the top of the list. The result indicates that when commenting on international sports events online, most spectators will identify themselves as team fans, which is consistent with the previous research conducted by Garland (Garland, 2004).
The performance of the team or players affects their fans’ satisfaction and ultimately affect fans’ loyalty (Shin, Park, Lee, & Kwon, 2010). In Table 2, the high-frequency words related to the team’ s performance in football events were "Player", "Wu Lei", "Level", and so on. In Fig. 1, the words "Country", "Team" and "China" were co-existing with "Player", in which it showed that the excellent performance of the team or player will increase the satisfaction of the fans, and then enhance their loyalty. This is consistent with previous study (Chung, Brown, & Willett, 2019). However, some scholars believe that for teams with a long history and better fan culture, even if their performance is poor, their fans will still maintain a high degree of loyalty, even the worse team's performance leads to higher fan loyalty (Campbell, Aiken, & Kent, 2004). Therefore, for the Chinese Men's National Football Team, in addition to achieving excellent competition results, creating a good fan atmosphere and fan culture also needs to be paid much attention to by managers.
When fans express a positive attitude towards the team, they will spontaneously take positive actions to support the team, thus affecting the neutral fans around them (Özgen & Argan, 2017). In Fig. 1, the word, "Cheer", also showed highly frequent usage. What appears with it were "China" and "Chinese Men's National Football Team", which proved that point of view. In addition, when the fans have a high degree of support, they will pay attention not only to the match of their own team, but also to the match of their opponents (Tapp, 2004). The high frequency of the words "Syria", "Japan", and "Maldives" in Table 1 also confirms this view. While to support the Chinese Men's National Football Team, fans will also pay attention to other teams’ matches, which is different from the traditional concept of football fans (Parker & Stuart, 1997).
Table 3 indicated that positive emotions account for more than neutral and negative emotions in comments on the performance of the Chinese Men's National Football Team in the 2022 FIFA World Cup Qualification, which showed that for the Chinese Men's National Football Team, the loyalty of most fans remained at a good level. In recent years, China's sports strength has been continuously enhanced, and it also has made remarkable achievements in international competitions. There is a positive relationship between sports success and the improvement of fans' loyalty (Bee & Havitz, 2010). Positive emotions can lead to an increase in fan loyalty. However, negative emotions still exist. The development level of football, basketball and other sports in China generally lags behind that of European countries and American. Therefore, football team managers should enhance the competitiveness of these sports, narrow the gap with other high-level countries, and break cultural anxiety to prevent the growth of negative emotions.
As can be seen from Table 5, among the four dimensions of the comments on the performance of the Chinese Men's National Football Team in the 2022 FIFA World Cup Qualification, the emotional of fan satisfaction is the closest to the overall proportion, indicating that fan satisfaction has a great impact on fan loyalty, which is consistent with Szymanski and his colleague’s research (Szymanski & Henard, 2001).
In the comments on the performance of the Chinese Men's National Football Team in the 2022 FIFA World Cup Qualification, the highest proportion of positive emotion is the Fan attitude loyalty factor. Positive emotion accounted for 50.21%. The more loyal the fans are, the more they will resist the change of identity and are more likely to act in favor of the team (Funk & James, 2001). Among the Fan attitude loyalty factor, after investigating the original data, it is found that most of the spectators in the positive mood have a positive attitude because of China's victory over Maldives and Syria. Some also have neutral or negative emotions because the Chinese Men's National Football Team is not as good as that of the Japan Men's National Football Team in the same group. Guo's research also shows that football has a very strong influence, and the current situation of a team can influence the mood and attitude of fans (Guo, 2018). The second highest proportion of positive emotion is the Fan identity factor, accounting for 48.91%. Due to the excellent performance in international competitions, the spectators showed a high sense of belonging, pride and identity to the Chinese Men's National Football Team, which are important factors to improve fans' loyalty (Li, 2007). In addition, some scholars believe that excellent matchs results can not only improve fans' identity with the team, but also strengthen the national identity sense (Henry, 2005).
The proportion of positive emotion of the above two factors is higher than that of the overall positive emotion, so for the performance of the Chinese Men's National Football Team in the 2022 FIFA World Cup Qualification, Fan attitude loyalty factor and Fan identity factor are the core elements of fan loyalty.
For negative emotions, the highest proportion of factors is the Fan behavior loyalty, accounting for 27.61%. The Fan behavior loyalty factor reflects whether people will support the team, maintain the team's image, and persuade others to support their favorite team (Gladden & Funk, 2010; Funk & James, 2001). As the Maldives Men's National Football Team is weak and the Syrian Men's National Football Team has been guaranteed to qualify, some spectators have not expressed a high sense of identity for the victory of the Chinese Men's National Football Team, but are pessimistic about its future. At the same time, due to the long-term weakness, some spectators lack a sense of identity with the Chinese Men's National Football Team and hold a negative attitude towards its image (Ma & Zhang, 2006). The second factor is Fan satisfaction factor, accounting for 24.63%. The performance of players and the team are presented directly in front of the audience in the game. When the players or teams do not perform well, it will affect the satisfaction of the fans and further affect the loyalty of the fans (Ksenija, 1995). There is a positive relationship between fan satisfaction and fan loyalty. In addition, the research of Paul found that fan satisfaction is an important measure of team attendance, audience rating and income (Paul, Wachsman, & Weinbach, 2011).
Therefore, for the performance of the Chinese Men's National Football Team in the 2022 FIFA World Cup Qualification, Fan behavior loyalty factor and Fan satisfaction factor are the main factors that affect the improvement of fan loyalty.
This study used big data mining to obtain online comments on the performance of the Chinese Men's National Football Team in the 2022 FIFA World Cup Qualification. Data were analyzed with the methods of high-frequency word analysis, semantic network diagram analysis, and emotion analysis to explore the influencing factors of fan loyalty.
From the study result, it found that the proportion of positive emotion (43.07%) was higher than that of neutral emotion (33.58%) and negative emotion (23.35%). The high positive mood showed that most spectators were satisfied with the performance of the Chinese Men's National Football Team in the 2022 FIFA World Cup Qualification. The fact that the neutral emotion was higher than the negative emotion meant that spectators commented on the Chinese Men's National Football Team from an objective and fair perspective.
Besides, it was found that the factors that affect fan loyalty from high to low were: Fan attitude loyalty factor (50.21%), Fan identity factor (48.91%), Fan behavior loyalty factor (41.74%), Fan satisfaction factor (41.38%). The factor that had the highest influence on fans' loyalty was Fan attitude loyalty, which fully showed that most fans were optimistic about the future of Chinese Men's National Football Team. When compose comments, spectators identify themselves as Chinese Men's National Football Team fans, maintain high fan loyalty, and have a strong sense of belonging, identity and pride to the team. At the same time, they will spontaneously maintain the image of the team on the Internet, and make an objective and fair evaluation. The factor that had the lowest influence on fan loyalty is Fan satisfaction factor, because the performance of the Chinese Men's National Football Team in the 2022 FIFA World Cup Qualification is not as expected, which leads to the dissatisfaction of some fans.
First of all, the research results help the team managers to understand the fans' loyalty to the team, so as to strengthen the contact and interaction with fans through the network to enhance the fans' loyalty to the team.
Secondly, this study proposes a convenient and reliable method to measure or evaluate the loyalty of fans. The online comments data of fans are crawled on the Internet, and the overall evaluation of fan loyalty is made from four aspects: fan identity factor, fan satisfaction factor, fan attitude loyalty factor and fan behavior loyalty factor.
Finally, as there is a close relationship between fan satisfaction and loyalty, managers should strengthen the technical and tactical training of players, train football stars, improve the competitiveness of the team, and enhance the loyalty of fans with excellent performance in matches.
First of all, there is no access to collect comments data from fans who are unwilling to express their views on the Internet.
Secondly, this paper only takes the 2022 FIFA World Cup Qualification (Asian Division) as an example, the research conclusion cannot be extended to other football matches.
Availability of data and materials
The datasets generated during the current study are not publicly available, but are available from the corresponding author upon reasonable request.
Acknowledgments
Author Contributions: All authors contributed to this manuscript and approved the final version of the manuscript.
Funding: This study was funded by the National Social Science Fund of China (No.21BTY063).
Conflict of Interest: The authors declare that they have no conflict of interest.